Perceptions Toward Artificial Intelligence (AI) Among Animal Science Students in Chinese Agricultural Institutions—From Perspectives of Curriculum Learning, Career Planning, Social Responsibility, and Creativity

Abstract

As artificial intelligence (AI) technology continues to advance and iterate, various industries have undergone intelligent reformation. China’s animal husbandry industry, given its importance for people’s livelihoods, is no exception to this transformation. Using AI technology in this field is becoming increasingly common since it not only improves production efficiency but also revolutionizes traditional business models. Animal science is a fundamental discipline that drives the progress of animal husbandry by studying the growth, breeding, nutritional needs, and feeding management of livestock and poultry. This discipline also explores advanced veterinary theories and technologies for epidemic prevention and control. The ultimate objective of this discipline is to ensure the production of high-quality and sufficient animal products to fulfill the demands of both production and daily life. It is predicted that the deep integration of AI technology into animal science will bring unprecedented opportunities to the animal husbandry industry. This study aims to explore the impact of artificial intelligence (AI) on students’ learning experiences and future educational directions. By situating the research within the context of current developments in educational technology, we hope to provide valuable insights for educators and policymakers and employ a questionnaire survey to explore the perceptions and attitudes of students majoring in animal science from various agricultural institutions in China toward this integration. The results of the study provide valuable and practical references for the cultivation and development of artificial intelligence talent in China’s livestock industry.

1. Introduction

Animal science discipline covers a broad range of areas, including animal physiology, animal genetics, animal ethology, and animal nutrition [1]. It requires students to possess a strong scientific foundation and a blend of theoretical knowledge and practical skills. At present, artificial intelligence (AI), an interdisciplinary technology, has progressively been penetrating into the field of animal husbandry [2]. Its application in agriculture spans planting, breeding, processing, and other sectors, providing innovative solutions to improve agricultural productivity, reduce costs, and protect the ecological environment [3]. Against this background, it becomes particularly important to assess the perceptions and attitudes of students majoring in animal science at agricultural institutions toward AI. This assessment will be conducive to optimizing the curricular design and training models in agricultural institutions, as well as promoting the development of scientific research. It will also provide guidance for students’ career development and, to a certain extent, enhance their social responsibility and creativity. In November 2022, the launch of ChatGPT (version 3.5), an advanced AI chatbot program developed by OpenAI, marked the second climax in AI advancements, following the precedent set by AlphaGo’s victory over the world Go champion Lee Sedol [4]. Applying AI to animal production presents extensive potential. Ezanno P et al. have demonstrated the multifaceted utility of AI in animal health (AH) [5]. Specifically, AI is instrumental in forecasting epidemiological trends in animals, advancing precision medicine for both animals and humans and elucidating the intricate interaction between hosts and pathogens [6]. In addition, the technological advancement of AI can improve the diagnostic accuracy for animal diseases, thereby enhancing the precision and reliability of prediction [7]. Additionally, AI is able to simulate complex biological systems with greater fidelity, offering a diagnostic basis for experts. Meanwhile, it can speed up the decision-making process, improve the accuracy of risk analysis, and enable more targeted interventions [8]. In a recent study conducted by Bhuiyan T et al. at the University of South Florida, AI algorithms have been trained to classify bees, hornets, and various bee mimics [9]. Nevertheless, its integration in animal husbandry raises pertinent questions regarding its potential impact on the quality of tertiary education for animal science, as well as the possibility of AI replacing traditional manpower [10].

In recent years, the application of artificial intelligence (AI) technology in the field of animal science has become increasingly widespread, covering various aspects from precision livestock farming to animal health monitoring and genomic analysis [4]. For instance, AI-driven image recognition technology has been utilized to automatically monitor animal behavior and health status, while machine learning algorithms have assisted researchers in analyzing complex genomic data to optimize breeding strategies. Additionally, AI has shown great potential in feed formulation optimization, disease prediction, and environmental management. The application of these technologies not only enhances production efficiency but also provides new solutions for animal welfare and sustainable development. In China, animal science education is gradually integrating emerging technologies, but the prevalence of AI-related courses remains limited [1]. Most animal science programs still focus on traditional disciplines such as animal nutrition, genetics, and reproductive science. However, with the rapid development of AI technology, an increasing number of educational institutions are beginning to recognize the importance of incorporating AI into their curricula. This study aims to explore animal science students’ awareness and acceptance of AI technology, as well as their perspectives on the application of AI in their future career planning. Globally, AI technology is rapidly transforming research and practice in agriculture and life sciences. AI can provide personalized learning content and feedback based on students’ learning progress, interests, and knowledge levels. For example, by analyzing students’ learning data, AI can recommend suitable learning resources or adjust the difficulty of teaching. AI-driven virtual assistants can offer real-time answers and guidance to help students better understand complex concepts. AI can create virtual lab environments that allow students to conduct practical operations such as animal dissection and disease diagnosis in a safe virtual setting, making up for the shortcomings of traditional laboratory resources. Through AI-powered simulators, students can practice skills like animal surgery and behavioral observation to enhance their practical abilities. AI can also help students analyze animal behavior, genetic data, or disease patterns to develop their data science skills. Additionally, AI can provide data-based decision-making suggestions, such as in animal nutrition management or disease prevention [6]. However, there are several limitations to this study. The sample primarily consists of animal science students from a few universities in China, and the sample size and geographical distribution may limit the generalizability of the results. Due to differences in educational resources and technological development levels across regions, the findings may not fully represent the overall views of animal science students nationwide. Future research could expand the sample size to include more regions and types of institutions to enhance the representativeness of the results. This study mainly collected data through questionnaires, which, while capable of quickly gathering a large amount of information, may also introduce subjectivity [7]. For example, students’ understanding of AI technology may be influenced by the wording of the questionnaire, leading to response bias. Additionally, questionnaires cannot delve deeply into students’ specific thoughts and experiences. Future research could incorporate qualitative methods such as in-depth interviews or focus group discussions to obtain more comprehensive data [8]. During the research process, we observed varying levels of understanding of AI technology among students, with some lacking a clear grasp of basic AI concepts and application scenarios. This may affect their views and attitudes toward the application of AI in animal science [9]. Furthermore, due to the complexity and rapid evolution of AI technology, the AI application cases discussed in this study may not fully reflect the latest technological advancements. This study was conducted within a specific timeframe and did not track long-term changes in students’ attitudes toward AI technology. As AI technology continues to develop and become more widespread, students’ views and acceptance may evolve. Future research could employ longitudinal studies to track changes in the same group of students at different points in time, providing a more comprehensive understanding of the impact of AI technology on animal science education.

Previous studies have shown that AI can improve the academic performance of students with learning difficulties and stimulate their enthusiasm and curiosity for learning. Personalized learning guidance can also be provided by ChatGPT to help them solve academic problems [11]. Additionally, the use of AI technology in classroom teaching has been reported to improve students’ attention levels [12]. From these results, it is evident that AI has a positive impact on students’ curriculum learning. Traditionally, teachers evaluate students’ grades based on the quality of their assignments, which reflects their academic performance. When students use ChatGPT to complete their assignments, it is difficult for teachers to determine their academic levels [13].

As for career planning, AI has had a profound impact on the entire animal husbandry industry, bringing both challenges and pressure to students majoring in animal science [14]. The wide application of AI technology is leading to the gradual demise of some jobs in traditional animal husbandry. In the meantime, it is also promoting the transformation and upgrading of jobs. Increasingly, jobs with low technical content are being replaced by AI technology. Since AI technology is continuously developing, more jobs are expected to be replaced in the future, making job upgrading a continuous and irreversible process [15]. As early as 1930, the British economist John Maynard Keynes proposed the term “technological unemployment”, which refers to unemployment caused by technological progress [16]. Currently, AI has been able to perform some tasks that were traditionally considered unique to human beings (non-routine and cognitive). As a consequence, students majoring in animal science face the threat of job replacement. In 2017, a study by Frey and Osborne from Oxford University evaluated the probability of automation replacing various occupations [17]. Their findings indicated that, out of a survey of 702 occupations, about 47% of occupations are at a high risk of being replaced by AI. Notably, an estimated 97% of agricultural and food science and technology personnel are expected to be replaced by AI. In light of the in-depth development of AI, employers are increasingly demanding the comprehensive quality of graduates majoring in animal science, especially their innovation ability [18]. It must be noted, however, that the conventional mechanistic education approach has been unable to meet the requirements of the AI era. Fostering creative thinking and innovation skills should be at the forefront of animal science education in the future, thereby leading the development of animal husbandry [19]. Furthermore, as AI develops and its improper applications spread, various social problems are emerging, infringing personal rights and endangering public order, which urgently needs standardized governance [20]. Therefore, it is important for Chinese higher education to cultivate students’ social responsibility and to guide them to establish correct attitudes and rational understanding toward AI [21].

In this study, we administered an anonymous survey to 170 students majoring in animal science from various agricultural institutions across China. The survey was distributed via a questionnaire, and 166 valid responses were collected. The questionnaire was carefully designed and included diversified questions associated with curriculum learning, career planning, social responsibility, and creativity. Building upon the foundational questionnaire data, we implemented a tripartite focus group protocol involving randomly stratified subgroups (6–8 participants per cohort, 120 min sessions) to investigate artificial intelligence’s multidimensional influences across four core domains: pedagogical engagement, professional trajectory development, societal accountability, and creative competency cultivation. The structured discourse analysis yielded empirically verified research outcomes through systematic triangulation. We propose to employ this questionnaire instrument complemented by focus group discussions to conduct a comprehensive assessment of artificial intelligence’s dual impact on academic achievement metrics and professional aspiration formation. The synthesized findings will facilitate evidence-based recalibration of pedagogical frameworks and curricular architecture through iterative design optimization. Findings from this study will offer references to enhance agricultural education at the tertiary level in China.

2. Materials and Methods

2.1. Materials

The main data utilized in this study were derived from the questionnaire survey conducted among students majoring in animal science from agricultural institutions across China. A total of 166 students participated in the survey, which was conducted online because students came from different provinces. To enhance the reliability of the survey instrument, we referenced and adapted a previously validated academic questionnaire. Specifically, we utilized the Likert scale to quantify the attitudes or opinions of participants and made appropriate modifications to adapt it to the specific needs of this study [21]. This step ensured the reliability and validity of the survey instrument. The questionnaire consisted of two parts. One part was designed to collect statistical characteristics of students’ personal demographics, including gender, grade, and domicile. The other part presented questions formatted on a Likert scale, prompting participants to score their agreement. The Likert scoring system was delineated from 1 (the lowest) to 5 (the highest). Specifically, a score of 1 corresponds to “strongly disagree”, 2 to “disagree”, 3 to “neutral”, 4 to “agree”, and 5 to “strongly agree”. Using this scale, the research objectives were strategically highlighted through quantitative data (Figure 1). Building upon the foundational questionnaire data, we implemented a tripartite focus group protocol involving randomly stratified subgroups (6–8 participants per cohort, 120 min sessions) to investigate artificial intelligence’s multidimensional influences across four core domains: pedagogical engagement, professional trajectory development, societal accountability, and creative competency cultivation. The structured discourse analysis yielded empirically verified research outcomes through systematic triangulation.

2.2. Methods

Given the differences in the educational models of agricultural institutions in different regions of China, the data obtained from the questionnaire were more reasonable when 170 animal science students were randomly and evenly sampled from these institutions. The questionnaire and in-depth interviews were designed to collect the views and perceptions of animal science students from these institutions on AI from the perspectives of coursework, career planning, social responsibility, and creativity. The questionnaire and in-depth interviews were carefully designed to explore students’ views and attitudes in depth from multiple perspectives, which will be crucial for comprehending the impact of AI on animal science education and its role in students’ future career development. Excel and SPSS 26.0 were used to perform a valid and reliable analysis of the collected data. Graphpad Prism 10 and Excel were employed for the drawing of pictures and tables. Although this study provides valuable insights, there are some limitations to consider. Firstly, the relatively small sample size may restrict the generalizability of the results. Secondly, data collection was confined to a specific region, which may not fully represent other educational contexts. Future research should consider expanding both the sample size and the geographical scope to enhance the universality of the findings.

3. Results

3.1. Population Characteristics

A total of 166 questionnaires were collected from animal science students from different agricultural institutions across China. The demographic data revealed that 89 male participants constituted 53.6% of the sample, and 77 female participants comprised 46.4%. The academic year distribution showed 40 first-year students (24.1%), 52 second-year students (30.7%), 44 third-year students (26.5%), and 31 fourth-year students (18.7%). Additionally, the data presented that 85 students (51.2%) originated from rural backgrounds, while the remaining 81 (48.8%) were from urban locales. Reliability analysis was conducted to assess the reliability and accuracy of the quantitative data, with a particular focus on the questions in the attitude scale. As shown in

Table 1. Cronbach’s reliability analysis.

Name	Total Correlation of Correction Items	Deleted Alpha Coefficient	Cronbach Alpha Coefficient
Gender	0.125	0.804	0.803
Grade	0.358	0.798
Registered residence	0.129	0.804
AI plays an important role in the development of animal husbandry	0.265	0.799
Do you understand the basic principles of AI	0.194	0.803
You are very familiar with AI-related terms	0.274	0.799
The rapid development of AI has more advantages than disadvantages	0.327	0.797
You often use AI (such as ChatGPT, etc.) to complete course assignments and learning tasks assigned by teachers	0.269	0.802
AI can improve your learning efficiency	0.460	0.791
AI can increase your learning motivation	0.418	0.793
AI technology will replace teacher instruction	0.021	0.823
Teachers should use AI in classroom teaching	0.425	0.793
Given the rapid development of AI, you will not work in the livestock industry	0.329	0.797
AI will create pressure and threats to your employment	0.468	0.790
AI teaching will benefit your career	0.444	0.791
AI can affect work, will you re-plan your future work	0.408	0.793
The government or relevant departments should take measures to regulate AI	0.366	0.795
AI will accelerate social polarization issues such as resource allocation	0.481	0.790
AI can cause the spread and leakage of personal privacy, posing significant security risks	0.521	0.788
The use of AI in scientific research processes will exacerbate ethical issues of academic misconduct	0.594	0.784
AI can inspire your creative thinking	0.525	0.788
AI can stimulate your imagination	0.494	0.789
When brainstorming, you prefer using AI over team discussions	0.458	0.790
AI cannot replace human creativity	0.264	0.800

Standardized Cronbach alpha coefficient: 0.821.

, the reliability coefficient is 0.803, which is greater than 0.8. This indicates the high reliability of the data and their suitability for subsequent analysis.

The KMO value of 0.776 was obtained using KMO and Bartlett’s test for validity validation. In

Table 2. KMO and Bartlett’s tests.

KMO Value	0.776
Bartlett sphericity test	Chi-square	1070.053
	df	276
	p value	0.000

, we can see that the KMO value ranges from 0.7 to 0.8, indicating the appropriateness of research data for extracting information and good validity.

AI technology has had a significant impact on the education of animal science majors. In

Table 3. Results of frequency analysis.

Name	Option	Frequency	Percentage (%)	Cumulative Percentage (%)
AI will play an important role in the development of animal husbandry	Commonly	18	10.84	10.84
	Agree	113	68.07	78.92
	Strongly agree	35	21.08	100.00
Do you understand the basic principles of AI	Disagree	15	9.04	9.04
	Commonly	110	66.27	75.30
	Agree	35	21.08	96.39
	Strongly agree	6	3.61	100.00
You are very familiar with AI-related terms	Strongly disagree	1	0.60	0.60
	Disagree	20	12.05	12.65
	Commonly	95	57.23	69.88
	Agree	45	27.11	96.99
	Strongly agree	5	3.01	100.00
The rapid development of AI has more advantages than disadvantages	Strongly disagree	1	0.60	0.60
	Commonly	41	24.70	25.30
	Agree	110	66.27	91.57
	Strongly agree	14	8.43	100.00
You often use AI (such as ChatGPT, etc.) to complete course assignments and learning tasks assigned by teachers	Strongly disagree	9	5.42	5.42
	Disagree	60	36.14	41.57
	Commonly	56	33.73	75.30
	Agree	35	21.08	96.39
	Strongly agree	6	3.61	100.00
AI can improve your learning efficiency	Disagree	2	1.20	1.20
	Commonly	38	22.89	24.10
	Agree	104	62.65	86.75
	Strongly agree	22	13.25	100.00
AI can increase your learning motivation	Disagree	1	0.60	0.60
	Commonly	41	24.70	25.30
	Agree	104	62.65	87.95
	Strongly agree	20	12.05	100.00
AI technology will replace teacher instruction	Strongly disagree	18	10.84	10.84
	Disagree	79	47.59	58.43
	Commonly	20	12.05	70.48
	Agree	44	26.51	96.99
	Strongly agree	5	3.01	100.00
Teachers should use AI in classroom teaching	Disagree	1	0.60	0.60
	Commonly	31	18.67	19.28
	Agree	115	69.28	88.55
	Strongly agree	19	11.45	100.00
Given the rapid development of AI, you will not work in the livestock industry	Strongly disagree	2	1.20	1.20
	Disagree	12	7.23	8.43
	Commonly	56	33.73	42.17
	Agree	86	51.81	93.98
	Strongly agree	10	6.02	100.00
AI will create pressure and threats to your employment	Disagree	5	3.01	3.01
	Commonly	26	15.66	18.67
	Agree	112	67.47	86.14
	Strongly agree	23	13.86	100.00
AI teaching will benefit your career	Disagree	2	1.20	1.20
	Commonly	27	16.27	17.47
	Agree	103	62.05	79.52
	Strongly agree	34	20.48	100.00
AI can affect work, will you re-plan your future work	Disagree	1	0.60	0.60
	Commonly	20	12.05	12.65
	Agree	110	66.27	78.92
	Strongly agree	35	21.08	100.00
The government or relevant departments should take measures to regulate AI	Commonly	17	10.24	10.24
	Agree	113	68.07	78.31
	Strongly agree	36	21.69	100.00
AI will accelerate social polarization issues such as resource allocation	Disagree	1	0.60	0.60
	Commonly	21	12.65	13.25
	Agree	100	60.24	73.49
	Strongly agree	44	26.51	100.00
AI can cause the spread and leakage of personal privacy, posing significant security risks	Commonly	20	12.05	12.05
	Agree	106	63.86	75.90
	Strongly agree	40	24.10	100.00
The use of AI in scientific research processes will exacerbate ethical issues of academic misconduct	Disagree	1	0.60	0.60
	Commonly	25	15.06	15.66
	Agree	96	57.83	73.49
	Strongly agree	44	26.51	100.00
AI can inspire your creative thinking	Disagree	2	1.20	1.20
	Commonly	22	13.25	14.46
	Agree	116	69.88	84.34
	Strongly agree	26	15.66	100.00
AI can stimulate your imagination	Disagree	2	1.20	1.20
	Commonly	31	18.67	19.88
	Agree	110	66.27	86.14
	Strongly agree	23	13.86	100.00
When brainstorming, you prefer using AI over team discussions	Strongly disagree	1	0.60	0.60
	Disagree	4	2.41	3.01
	Commonly	37	22.29	25.30
	Agree	105	63.25	88.55
	Strongly agree	19	11.45	100.00
AI cannot replace human creativity	Disagree	2	1.20	1.20
	Commonly	15	9.04	10.24
	Agree	98	59.04	69.28
	Strongly agree	51	30.72	100.00
Total		166	100.0	100.0

The frequency of 0 is not displayed in the table.

, we analyzed the questionnaire results from five aspects: attitude recognition, curriculum learning, career planning, social responsibility, and creativity. The research results indicate that artificial intelligence has significant potential in enhancing students’ learning motivation and personalized learning experiences. These findings support our discussion and conclusions, demonstrating the broad prospects for the application of artificial intelligence in the field of education.

3.2. Attitudes of Animal Science Students Toward AI

With broad applications in animal husbandry, reproduction, disease diagnosis, and more, AI is closely related to animal science. What do students in this discipline make of this technology? Our survey found that 89.15% of the respondents believe that AI contributes significantly to the development of animal husbandry, with no one opposing this idea. However, the number of respondents who answered “Yes” to the question “Do you understand the basic principles of AI?” is relatively low (24.69%). A total of 30.12% of the respondents claimed familiarity with AI-related terminology. Most respondents responded positively to the question “Is AI’s rapid development more beneficial than harmful?”, with 66.27% agreeing and 8.43% strongly agreeing, totaling 74.7%. Conversely, 25.3% of respondents held neutral or negative attitudes. In summary, students majoring in animal science exhibit a positive stance toward the application of AI technology in animal husbandry despite a noted deficiency in AI-related knowledge.

3.3. Academic Learning Aspects

The questionnaire survey revealed significant differences among respondents regarding the frequent use of AI, such as ChatGPT, to complete assignments. Specifically, 24.69% of respondents frequently used AI in their academic tasks, while 41.56% of them infrequently relied on it. Despite different opinions on the application of AI in academia, there is a general consensus that AI is able to improve learning efficiency. Over 75% of respondents (with 62.65% agreeing and 13.25% strongly agreeing) supported that AI enhanced their learning efficiency. Additionally, 74% of respondents, with 62.65% agreeing and 12.05% strongly agreeing, believed that AI could ignite their learning enthusiasm and motivate their greater engagement in academic pursuits. Regarding the notion that “AI technology will replace teachers’ lectures”, nearly 60% of respondents (with 47.59% disagreeing and 10.84% strongly disagreeing) considered it incorrect, while 26.51% of respondents agreed with this view. These findings underscore the prevailing belief among the majority of respondents regarding the indispensable role of teachers in the teaching process. Simultaneously, over 80% of respondents (with 69.28% agreeing and 11.45% strongly agreeing) advocated for the integration of AI technology by teachers in classroom teaching to improve teaching efficacy. Apart from different opinions on the appropriateness of AI for academic tasks, the majority acknowledged AI’s potential as an auxiliary tool to promote learning efficiency and stimulate students’ learning motivation, which emphasizes the significance and relevance of AI technology in course learning. Although AI is not seen as a substitute for teachers in the classroom, its utilization is perceived as a means to enrich the learning experience for students.

3.4. Career Planning Aspects

Regardless of the rapid development of AI technology, the majority of students favored employment in the livestock industry and considered that AI had a positive impact on their career prospects. This suggests that students recognize the potential of AI technology in their careers. Nearly 60% of respondents expressed a preference for pursuing careers in the livestock industry, indicating that AI has not substantially deterred students majoring in animal science from pursuing employment in the livestock industry. At the same time, over 82% of respondents believed that AI technology had a favorable influence on their future career prospects. However, a majority of respondents (81.33%) mentioned their concerns in terms of the potential negative effects, such as pressure and threat, from AI on their employment opportunities. Only 3.01% and 0% of respondents disagreed or strongly disagreed with the above concerns, respectively. Accordingly, more than 87% of respondents would consider re-planning their careers. In response to pressures and challenges posed by AI in the job market, 96.39% of respondents advocated for participating in relevant skill training or courses as the best way to enhance their core competitiveness, with 75.9% choosing to learn AI-related skills. Additionally, accumulating internship experience was also considered an effective way to improve core competitiveness, accounting for 25.3%. However, academic research or projects, as a potential avenue to improve their core competitiveness, were favored by fewer respondents (only 12.05%).

3.5. Social Responsibility Aspects

As a technology with broad application prospects and great development potential, AI has resulted in widespread social concerns. The primary issues are privacy protection and data security. The second one is the issue of fairness, which has become the forefront of discussion. This is because factors such as data bias and algorithmic discrimination may lead to unfair treatment of vulnerable groups despite the benefits and convenience brought by AI. In academic research, the quality and quantity of data directly affect model performance when utilizing AI technology. Ethical concerns related to intellectual property rights may arise during data acquisition, processing, and application. This study explored the awareness of students majoring in animal science regarding the social responsibilities triggered by AI through a questionnaire survey. Results indicate that 89.76% of respondents support the implementation of regulations governing AI technology. Additionally, 86.75% of respondents were concerned that AI may exacerbate social polarization, such as the allocation of social resources, compared with only 0.6% of respondents disagreeing with this view. Regarding the risks that AI posed to personal privacy, 12.05% of respondents were neutral, while 63.86% agreed with the concerns raised. Notably, 24.1% of respondents highly agreed with the notion. Students’ knowledge and attitudes toward these social issues raised by AI, such as privacy protection, data security, and fairness, reflect their understanding and commitment to the social responsibility of AI. In scientific research, the use of AI may intensify ethical issues of academic misconduct. The distribution of different attitudes was as follows: strongly disagreeing was 0%, disagreeing was 0.6%, neutral was 15.06%, agreeing was 57.83%, and strongly agreeing was 26.51%. Overall, the majority of students supported the implementation of regulations governing AI technology, which emphasizes the importance of fostering awareness of AI ethics and social responsibility in education.

3.6. Creativity Aspect

Creativity has been increasingly considered a core competency in the 21st-century education system. With the gradual application of AI in education worldwide, an essential issue has arisen regarding students’ perceptions of the relationship between AI and creativity. Results of the questionnaire presented that the majority of students believed AI has a positive impact on their creative thinking and imagination. Specifically, 85.54% of respondents believed that AI can inspire their creative thinking, and 80.13% felt that AI can stimulate their imagination. Conversely, only 1.2% of respondents held a negative view of AI. When faced with the task of brainstorming, as high as 74.7% of respondents indicated a preference to rely on AI assistants over discussing solutions through team collaboration. A smaller percentage of 22.29% remained neutral on this matter, while only 4.61% of respondents expressed a reluctance to utilize AI technology. Regarding the potential of AI to replace human creativity, 89.76% of respondents either agreed or somewhat agreed, contrasting with only 3.2% of respondents who disagreed or strongly opposed this notion. Additionally, 15 students (9.04%) took a neutral stance. Moreover, the three most effective ways that AI enhances creativity are an open and exploratory learning environment, time-saving searching for foundational knowledge, and personalized teaching and learning recommendations. Overall, students recognized the positive impact of AI on creativity to a certain degree. However, the potential effects of AI on students’ collaboration skills and independent thinking capacity should not be ignored. While AI can assist with idea generation, greater emphasis should be placed on maintaining and developing students’ independent thinking skills. In other words, educational practice needs to strike a balance between the use of AI and developing students’ creativity and independent thinking skills.

4. Discussion

As technology advances at an accelerated pace, AI technology has been gradually penetrating into various fields. Notably, its integration with the animal science discipline has brought unprecedented opportunities and challenges to both disciplines [22]. For students specializing in animal science, AI can not only reshape their learning methods but also offer them new research tools and career development opportunities [23]. According to a systematic collection and analysis of the related literature, students specializing in animal science have been reported to rely on traditional textbooks and laboratory practices to learn in the past. However, the emergence of AI has changed this situation. Currently, students can engage in learning through online courses and virtual laboratories [24] that combine AI technology to simulate authentic experimental environments for students to practice [25]. These ways of learning can not only increase learning flexibility but also save time and cost. AI has also offered animal science researchers powerful tools [26,27]. For example, machine learning algorithms enable researchers to reveal patterns and regularities in animal behavior by analyzing a large amount of data [28,29,30]. Another example is its application to improve the efficiency of animal husbandry management schemes, thereby improving animal welfare and production efficiency [31]. These tools have enabled researchers to comprehend the physiological and behavioral mechanisms of animals thoroughly and to make greater contributions to the development of this discipline [32,33].

As AI applications in animal science continue to expand, so does the demand for professionals with relevant competencies. To a certain extent, AI has brought diversified advantages to students’ learning in terms of curriculum study, career planning, social responsibility, and creativity. Therefore, students specializing in animal science are presented with more career development opportunities. By obtaining knowledge and skills related to AI, students can become more versatile and competent with both knowledge and skills in animal science and technology [34,35]. These students will have promising employment prospects in diverse fields, such as animal science, biotechnology, and veterinary medicine. While AI brings many opportunities, it also presents some challenges. For instance, the pervasive adoption of AI technology has engendered the automation of certain traditional roles in this field [36]. In response to these changes, it is pivotal for students to plan their careers proactively and enhance their holistic competencies to align with the evolving demands of the industry. However, facing the practical execution of career planning, some students are fraught with perplexity and apprehension concerning their career pathways.

From the perspective of curriculum learning, the curriculum of the animal science discipline was previously limited to traditional areas, such as animal genetic breeding, nutrition, and veterinary medicine, without any content related to AI. Students had little exposure to new technologies, and their access to learning AI was limited to occasional academic lectures or self-study [37]. This lack of a systematic learning framework has made it difficult for students to integrate AI skills with their professional knowledge. They were also easily daunted by the complex algorithm principles and had no way to start with practical applications. As a result, their knowledge structure was quite monolithic, making it difficult to meet the needs of agricultural science and technology in the new era.

With the recent maturation of AI technology, some agricultural institutions have gradually incorporated AI-related courses into the curriculum plan of animal science majors [38]. For example, elective courses like “Applications of Agricultural Big Data and Artificial Intelligence” and “Intelligent Aquaculture Technologies” have been offered. These courses cover cutting-edge and practical knowledge, such as the fundamental principles and skills of machine learning, the application of image recognition in the monitoring of animal husbandry, and the operation of intelligent livestock equipment. By combining theoretical explanations with practical operations, students can understand how AI empowers animal breeding, disease diagnosis, feed formula optimization, and other aspects.

In terms of teaching methods, teachers frequently adopt the project-driven approach. For example, teachers assign tasks such as “Constructing a Prediction Model for Livestock Growth Based on AI” and encourage students to complete them in groups. These tasks can exercise students’ programming skills, enable them to practice algorithms’ applications and improve their problem-solving abilities [1]. Meanwhile, the virtual simulation software can simulate intelligent farming scenarios, resulting in increased classroom interactions and enhanced learning interests.

From the perspective of career planning, the career choices of animal science graduates in the past were mostly confined to traditional positions such as aquaculture technicians, feed salespersons, and veterinarians. These relatively fixed career paths were often accompanied by slow salary growth. The reason behind this situation is that they failed to foresee the impact of AI on the industry and lacked forward-looking career planning. When the transformation of intelligent aquaculture came, their skill deficiencies became prominent, resulting in limited chances of promotion and only passive adaptation to the technological updates of enterprises. Under these circumstances, career transitions became extremely difficult, causing them to miss out on many emerging development opportunities [4].

Nowadays, influenced by the changes in the industry, students majoring in animal science are increasingly interested in AI-related positions in their career plans. A survey shows that more than 30% of students are captivated by emerging careers such as intelligent aquaculture engineers and animal health data analysts. In these positions, they expect to use AI technology to optimize the aquaculture process, tap the value of animal health data, and improve the economic benefits and competitiveness of farms [5]. When discussing the positive impacts of artificial intelligence, we further explored the specific contexts and conditions under which these effects occur. For instance, the effectiveness of AI in personalized learning is highly dependent on teachers’ technological proficiency and the resource support available in schools. Therefore, achieving these positive outcomes requires a comprehensive consideration of various factors, including technology, teacher training, and policy support. At the same time, the feedback from internships and placements has prompted students to adjust their plans. Many large-scale agricultural and animal husbandry enterprises have established intelligent aquaculture R&D departments and are recruiting animal science talents who are proficient in AI. This market change has made students realize the importance and advantages of interdisciplinary knowledge reserves. In order to secure a more favorable position in the emerging career field, they are actively participating in AI skills training and competitions to obtain relevant certificates [6].

From the perspective of social responsibility, students majoring in animal science were mainly concerned with increasing animal production to meet the growing demand for meat, eggs, and milk due to population growth while ignoring issues such as impaired animal welfare and environmental pollution during the production process. As society has developed, this old mindset has become unsustainable [7]. The limited knowledge of former students makes them powerless when promoting the green transformation of the aquaculture industry and balancing production efficiency with social responsibility. In contrast, current students with an in-depth understanding of AI can view the development of the industry from a more macro and holistic perspective and take an active role in social responsibilities. Currently, under the advocacy of animal welfare, students have realized the contribution of AI to precision farming and the reduction in stress caused by manual operations. For example, intelligent feeding systems can adjust the feeding amount in real time according to the animals’ feeding behaviors [8]. This kind of system ensures the supply of nutrients and avoids overfeeding, thus improving the living quality of animals and demonstrating humanitarian care.

In terms of environmental protection, students have recognized that AI-optimized feed formulas can reduce nitrogen and phosphorus emissions. In addition, intelligent ventilation and temperature control systems can improve the efficiency of energy utilization and facilitate the sustainable development of agriculture [39]. As a result, they actively participate in relevant research projects and club activities, as well as being committed to promoting the concept of AI-enabled green farming and popularizing the key points of technological applications among farmers so as to drive the whole industry to better fulfill its social responsibilities [40].

Moving on to the perspective of creativity, traditionally, students majoring in animal science have focused their innovations on the optimization within this discipline, such as improving breeding methods and developing new veterinary drugs. However, these innovations have limitations due to the homogeneity of the discipline, resulting in students’ confined thinking. Interestingly, the introduction of AI has overcome limitations and offered brand-new tools and perspectives. In the past, it was difficult to realize innovations in complex systems when there was a lack of big data processing and application of smart algorithms [13]. Nowadays, AI technology has greatly unleashed students’ creativity, giving rise to multiple new paradigms for solving agricultural problems.

As AI technology continues to mature, students’ innovative thinking has been inspired. They attempt to use cutting-edge technologies to solve traditional animal science problems. Examples include using deep learning algorithms to analyze animal sounds and behavior patterns, developing early warning systems for diseases, and innovatively solving the problems of disease prevention and control. By leveraging generative adversarial networks, they successfully designed new types of feed ingredients and expanded the ways of resource utilization [13]. Meanwhile, interdisciplinary teamwork has become frequent, with students majoring in animal science, computer science, and engineering working together in teams. This collaboration and collision of different knowledge have given birth to creative projects such as “intelligent wearable livestock devices” and “unmanned aquaculture inspection robots”. These projects have stood out in innovation and entrepreneurship competitions, demonstrating the strong creative vitality of students [16].

However, the integration of AI and animal science discipline has also brought about a multitude of ethical and moral issues. In animal behavior analysis, for example, the utilization of AI technology requires stringent safeguards to ensure the privacy and security of the data [41]. Similarly, the application of AI technology in the formulation of animal husbandry management systems should pay special attention to the welfare and ethical issues of animals [42,43]. Therefore, it is necessary for students to possess a strong ethical sensibility and social responsibility to ensure that the application of AI technology in animal science benefits both humans and animals [40].

5. Conclusions

The animal science discipline is undergoing a paradigm shift driven by AI technology due to AI’s exceptional potential for handling complex data, real-time monitoring, and behavioral analysis. This trend requires students to possess interdisciplinary knowledge and skills in computer science, statistics, and biology. It is therefore significant for educational institutions to understand how students perceive this integration, which will be conducive to adapting their curricula to cultivate researchers and practitioners. Apart from transforming educational paradigms and pedagogical philosophies, AI has contributed to the transformation of the educational ecosystem. By investigating students’ attitudes toward the integration of AI and animal science, it is possible to assess whether the current educational system is able to adapt to these changes and promote necessary educational reforms. These reforms will enable students to take full advantage of AI technology to enhance their learning efficiency and innovative capabilities.

In zoological research, the use of AI has not only improved the efficiency and accuracy of research but also driven a shift from descriptive to predictive and explanatory modeling. Students’ perceptions of AI integration may influence their choices of research methods and decisions about future career paths, making it important to investigate this topic to guide students’ career planning and cultivate their research interests. Using AI in animal welfare monitoring and experimentation has also raised prominent ethical issues. By understanding students’ acceptance of these technologies and ethical considerations, educational institutions can prioritize ethical education and social responsibility in the talent cultivation process. However, there are several limitations to this study. The sample primarily consists of animal science students from a few universities in China, and the sample size and geographical distribution may limit the generalizability of the results. Due to differences in educational resources and technological development levels across regions, the findings may not fully represent the overall views of animal science students nationwide. Future research could expand the sample size to include more regions and types of institutions to enhance the representativeness of the results.

By tracking students’ perceptions over time, educators can identify learning gaps and adjust their teaching strategies accordingly. For example, if students struggle to grasp a specific concept, educators can leverage AI-based tools to provide additional explanations or examples. As artificial intelligence becomes increasingly prevalent in the field of animal science, it is crucial for students to develop digital literacy skills. By incorporating AI-powered tools in education, students can familiarize themselves with these technologies and become better prepared for their future careers. Looking ahead, research and practice in the field of animal science will increasingly rely on AI technology. By understanding students’ attitudes toward AI integration, educational institutions can better prepare students with the necessary skills to address future career challenges such as data processing, model building, and interdisciplinary collaboration. In summary, the continuous integration of AI technology in the animal husbandry industry will give rise to both opportunities and challenges for students majoring in animal science at agricultural colleges and universities in China. Understanding students’ knowledge and attitudes toward this integration can offer significant references for the cultivation and development of experts with AI technology in agriculture and animal husbandry, thereby ultimately promoting intelligent transformation in this industry.