Core competencies in pharmaceutical education: a Chinese student perspective

Abstract

Background

From the students’ perspective, the research evaluates their views on core competencies and their own developmental needs within pharmaceutical education, attempting to explore potential pathways for optimizing students’ core competencies. This study seeks to enhance students’ core competencies, enrich learning and development theories, and establish a basis and reference for cultivating high-caliber pharmaceutical talents.

Methods

Establishing a core competency index system for pharmacy major, a survey questionnaire comprising 41 items across four dimensions (knowledge, skills, abilities, and values) was designed. Using stratified cluster sampling, 919 valid responses were collected. Descriptive statistics, variance analysis, and chi-square test were used to analyze the perceptions of pharmaceutical students on core competencies’ importance for professional growth and their satisfaction with teaching, and to examine disparities in the development of core competencies among different groups of students.

Results

The study revealed deficiencies in pharmaceutical students’ core competencies regarding artificial intelligence, pharmaceutical application, medical care, etc. Differential analysis indicated that significant differences across education levels: undergraduates prioritized foundational knowledge and ethical norms, while postgraduates emphasized project-based learning and ability improvement. Students with work or project experience placed higher value on knowledge application, systematic thinking, strategic capabilities, and innovative technologies such as artificial intelligence.

Conclusion

This study evaluates pharmaceutical core competency education from the student perspective, revealing their perceptions of developmental requirements. The research proposes an optimization pathway: the curriculum reform of pharmaceutical higher education should be scientific, general, innovative, practical and humanistic, thereby providing a reference for reforming pharmaceutical higher education.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12909-025-07686-7.

Background

With the advent of the information technology and knowledge economy era, interactions between individuals and society have grown increasingly complex and diverse. This phenomenon has not only given rise to novel business models, ideas, and perspectives but has also triggered inevitable conflicts in cognition, interpersonal relationships, interests, and emotions. Consequently, heightened demands are placed on individuals’ comprehensive competencies [1], transforming the substance of talent cultivation into a richer, more profound, and more purposeful endeavor.

The evolution of “core competency” has progressed through the embryonic stage, initial stage and expansion stage, characterized by increasing diversification and systematization. UNESCO’s 1996 proposal of the Four Pillars of Lifelong Education—Learning to Know, Learning to Do, Learning to Be, and Learning to Live Together—established a robust theoretical foundation for competency development [2]. In 1997, the Organization for Economic Co-operation and Development (OECD) initiated the Definition and Selection of Competencies: Theoretical and Conceptual Foundations project (DeSeCo), which first formalized the concept of key competencies. This framework identifies three core competency categories: interactive use of tools, autonomous action, and interacting in socially heterogeneous groups, emphasizing interpersonal dynamics and human-society interconnections [3].

Since the turn of the 21st century, more countries and organizations have begun to pay attention to and establish unique core competencies index system. In 2002, the United States launched the 21st Century Core Competencies Research Project [4]. Subsequently, the European Union issued the Key Competences for Lifelong Learning: European Reference Framework (2005) [5], establishing benchmark standards for EU education policies. France’s Common Foundation Act defined core competencies as the essential knowledge integration required in the modern era.

The research connotation of core competencies is constantly enriched. To proactively address future social challenges and global education competition, China launched the research and development of core competencies in 2013. In 2014, China’s Ministry of Education issued Guidelines on Deepening Reform of Student Evaluation Systems [6]. The concept of “core competency” appeared for the first time, clearly defining “research and formulation of core competency system and academic quality standards for student development” as the key field and main link to improve the level of talent education [7]. The Core Competencies for Chinese Student Development framework, was officially released in 2016, which refined and established six core competencies for college students, namely “humanistic heritage, scientific spirit, learning to learn, healthy living, responsibility, and practical innovation”.

Drawing on domestic and international research, this paper defines “core competencies” as the fundamental and critical abilities that individuals should possess across knowledge, skills, attitudes, and values. These competencies are essential character traits and key capabilities required for personal lifelong development and social progress [8], characterized by guidance, integrity, timeliness, and developmental adaptability.

The pharmaceutical industry is crucial to human health and life safety, which means pharmacy students must acquire both specialized domain expertise and a wide range of professional skills, as well as outstanding abilities [9]. In 2012, the International Pharmaceutical Federation (FIP) proposed the “Global Competencies Framework for Pharmacy” (GbCF), categorizing pharmacist competencies into: Pharmaceutical Public Health Competencies, Pharmaceutical Care Competencies, Organization and Management Competencies, and Professional/Personal Competencies [10], which provided reference standards and directions for the cultivation of pharmaceutical talents in various countries. However, there are differences in the implementation priorities in different regions. The Accreditation Council for Pharmacy Education (ACPE) adopted updated Pharmacy Professional Accreditation Standard in June 2024, establishing a student-centered, competencies-based training model [11], which prioritizes patient-focused care and interdisciplinary collaboration [12]. UK pharmacy education emphasizes clinical pharmacy knowledge, practical training, and professional ethics to cultivate practice-ready pharmacists [13]. In Japan, the Model Core Curriculum (MCC) standard for pharmacy education has been established, strong communication skills and self-study skills are regarded as fundamental qualities required of pharmacists [14]. With the development of core technologies such as big data, cloud computing, and artificial intelligence driving industrial intelligence, AI-assisted target discovery and virtual screening have significantly shortened the preclinical research cycle, demanding new requirements for the development of pharmaceutical students. Previous researchers have used coding analysis methods to propose new requirements for the core competencies of future talents in intelligent contexts, including basic employability, professional competence, and sustainable development ability [15]. There are also studies that identified the elements of research reports on the cultivation of scientific and technological talents, constructing a core competency framework that includes disciplinary literacy, system literacy, computational literacy, information literacy, and ethical literacy [16].

In general, current research on core competencies predominantly draws on theoretical aspects such as international reports that highlight industrial development and technological advancements, while empirically validated analyses remain limited [17]. There is a lack of special research from the perspective of students, particularly regarding core competency frameworks for pharmacy students aligned with China’s New Era development requirements. A measurable gap exists between expert expectations and students’ actual perceptions of core competency evaluation indicators. In this context, this study employs Chinese pharmaceutical universities as examples, deeply explores the students’ perceptions of the importance of core competencies such as knowledge, skills, abilities and values, comprehensively evaluates the teaching satisfaction of pharmaceutical professional education, provides research basis for pharmaceutical universities to optimize professional talent training scheme, and provides reference ideas for enhancing pharmaceutical educational situation.

Methods

This cross-sectional study employed literature review and expert interviews to develop a survey instrument based on the 13 core competencies for undergraduate pharmacy education. The questionnaire utilized a five-point Likert scale (1 = least important to 5 = most important). We administered this survey to second- and third-year undergraduates, graduate students, and in-service students. Through rigorous data cleaning and validation processes, we conducted multiple analytical procedures, including descriptive statistical, ANOVA, and chi-square tests to analyze status of students’ core competencies.

Questionnaire overview

The questionnaire is divided into two primary sections. While the first collects basic demographic data, the second evaluates how students perceive core competencies essential to pharmaceutical education—including their assessment of core competencies’ importance for professional growth and satisfaction with teaching.

The core competencies were structured hierarchically across three levels

First-level indicators

Knowledge, Skills, Abilities, and Values. Knowledge forms the foundation of core competencies. Skills represent the practical implementation of acquired knowledge. Abilities denotes stable psychological characteristics that facilitate effective task performance. Values determine an individual’s interactions with others, society, and nature. Collectively, these indicators—knowledge, skills, abilities, and values—form the comprehensive dimensions of core competencies.

Second-level indicators

Knowledge was categorized into several domains—mathematics, pharmacy, biology, information technology, management, and humanities. The Skills component emphasized areas such as problem identification and analysis, application tools, and management methods. In the Abilities dimension, the framework addressed individual internal abilities, interpersonal skills, and sustainable development skills. The Values component distinguished between professional norms & Pharmacy and Society.

Third-level indicators

These optimized the second-level indicators and further detailed the second-level categories by specifying particular competencies domains—such as specialized knowledge necessary for pre-clinical research, clinical trial design and implementation, pharmaceutical production processes, and therapeutic applications in clinical settings, including 10 knowledge, 12 skills, 13 abilities, and 6 values.

Questionnaire development process

The development of indicators was based on a review of relevant literature on advanced pharmaceutical talent development. In order to further ensure the scientific and practical fit of the indicators, two rounds of expert interviews were conducted. The first-round interview used a one-on-one method to explore in-depth the scientific content, disciplinary logic, and teaching operability of core competencies indicators (Supplement 1: Refer to the outline of interviews with pharmaceutical education experts). The second-round interview was conducted by engaging five senior pharmaceutical professionals, who were invited to optimize the indicators from an industry perspective (Supplement 2: Refer to the outline of interviews with high-level applied pharmaceutical industry talents). Based on interviews, research refers to the 13 core competencies of undergraduate students, and students’ basic situation and understanding of core competencies, we finally produced the final survey questionnaire. In addition, prior to launching the formal survey, researchers conducted a small-scale pilot study to evaluate the questionnaire’s effectiveness. The pilot study included 20 students with a grade ratio of 7 students in sophomore year, 7 students in junior year, 6 students with master’s degree or above. Participants completed standardized questionnaires under researcher supervision, with response times recorded. They subsequently provided feedback on: (a) Item phrasing refinement: In the Ability category, overlapping options were consolidated into the most precise items; (b) Response format optimization: Single-choice questions identifying knowledge/skill gaps were converted to multiple-choice format (≤ 3 selections) due to reported selection difficulty; (c) Indicator logic validation: Logical relationships between competency indicators were verified.

Questionnaire reliability and validity

Reliability

Reliability analysis was conducted to measure the reliability of the sample answers, and to test whether the data results collected by the questionnaire are consistent, which is manifested in the consistency of the results between the results of repeated measurements of the same trait object with the same measurement tool. The reliability of the questionnaire responses was assessed through Cronbach’s α coefficient. The reliability test results of the questionnaire results are shown in Table 1, the Cronbach’s α values for each dimension of the questionnaire are higher than 0.8, indicated a high degree of reliability. In order to avoid the problem of competencies redundancy, each item was deleted in turn, and it was found that the Cronbach’s α coefficient did not increase after deletion, so all items were retained.

Table 1.

Questionnaire reliability analysis

Research Dimensions		Indicators	Number of Qualities	Cronbach’s α coefficient
Importance for professional growth	Knowledge		10	0.83
	Skills		12	0.88
	Abilities		13	0.91
	Values		6	0.85
Satisfaction with teaching	Knowledge		10	0.89
	Skills		12	0.92
	Abilities		13	0.94
	Values		6	0.90

As can be seen from Table 2, the Pearson correlation coefficient between each item of the questionnaire and the total score of the importance for professional growth and the satisfaction with teaching is higher than 0.5, and the p-value is less than 0.01, indicating a strong correlation between each item and the total score.

Table 2.

Correlation coefficients between each index and the total score

		Item-total correlations (p-value)
		Importance for professional growth	Satisfaction with teaching
Knowledge	Computational and descriptive mathematical knowledge	0.62(p < 0.001***)	0.68(p < 0.001***)
	Pharmaceutical-related chemistry knowledge	0.53(p < 0.001***)	0.57(p < 0.001***)
	Knowledge of new equipment in pharmaceuticals	0.63(p < 0.001***)	0.69(p < 0.001***)
	Knowledge of new pharmaceutical processes and new technologies	0.59(p < 0.001***)	0.69(p < 0.001***)
	Knowledge of drug design, synthesis, formulation, and translation	0.54(p < 0.001***)	0.66(p < 0.001***)
	Biological knowledge of drugs	0.59(p < 0.001***)	0.68(p < 0.001***)
	Big data	0.70(p < 0.001***)	0.79(p < 0.001***)
	AI(artificial intelligence)	0.70(p < 0.001***)	0.78(p < 0.001***)
	Economic management of drugs	0.70(p < 0.001***)	0.76(p < 0.001***)
	Relationships between people and society	0.67(p < 0.001***)	0.74(p < 0.001***)
Skills	Apply mathematics and physics to logical reasoning and analysis	0.64(p < 0.001***)	0.7(p < 0.001***)
	Use chemistry for scientific analysis and judgment	0.66(p < 0.001***)	0.66(p < 0.001***)
	Apply pharmacy for in-depth understanding and scientific research	0.60(p < 0.001***)	0.65(p < 0.001***)
	Use biology for identification and application	0.61(p < 0.001***)	0.66(p < 0.001***)
	Use engineering knowledge to conduct systematic analysis and rationality demonstration	0.63(p < 0.001***)	0.73(p < 0.001***)
	Data skills such as data collection, refining, and processing (partial software)	0.64(p < 0.001***)	0.76(p < 0.001***)
	Use of modern analytical and testing instruments, qualitative and quantitative analysis (partial hardware)	0.67(p < 0.001***)	0.73(p < 0.001***)
	Use new technologies, new tools	0.67(p < 0.001***)	0.79(p < 0.001***)
	Research and judgment skills, risk assessment skills	0.70(p < 0.001***)	0.80(p < 0.001***)
	Systems thinking (full cycle, full process control)	0.72(p < 0.001***)	0.79(p < 0.001***)
	Grasp the rules of project operation	0.71(p < 0.001***)	0.77(p < 0.001***)
	Optimize the economic decisions of your engineering projects	0.68(p < 0.001***)	0.77(p < 0.001***)
Abilities	Time & Resource Management (Project-based)	0.70(p < 0.001***)	0.77(p < 0.001***)
	Forward-looking, strategic thinking and insight into the pharmaceutical industry	0.67(p < 0.001***)	0.77(p < 0.001***)
	Strong willpower to face the unknown	0.64(p < 0.001***)	0.78(p < 0.001***)
	User thinking with market ability	0.68(p < 0.001***)	0.80(p < 0.001***)
	Communication skills	0.73(p < 0.001***)	0.76(p < 0.001***)
	Teamwork (cross-border integration)	0.73(p < 0.001***)	0.76(p < 0.001***)
	Leadership	0.69(p < 0.001***)	0.80(p < 0.001***)
	Global competence	0.70(p < 0.001***)	0.80(p < 0.001***)
	Curiosity, continuous lifelong learning	0.72(p < 0.001***)	0.77(p < 0.001***)
	Metacognition, self-knowledge, self-reflection	0.74(p < 0.001***)	0.80(p < 0.001***)
	Knowledge transfer and problem-solving skills in complex contexts	0.70(p < 0.001***)	0.79(p < 0.001***)
	Ability to innovate, with a strong desire to break through the stuck neck technology	0.70(p < 0.001***)	0.81(p < 0.001***)
	Entrepreneurship and entrepreneurial ability	0.70(p < 0.001***)	0.79(p < 0.001***)
Values	cherish the greatness of the country	0.71(p < 0.001***)	0.77(p < 0.001***)
	Altruism, dedication	0.77(p < 0.001***)	0.83(p < 0.001***)
	Pharmaceutical Engineering Ethics and Norms	0.73(p < 0.001***)	0.82(p < 0.001***)
	Undertake health, safety, legal and cultural social responsibilities	0.78(p < 0.001***)	0.83(p < 0.001***)
	Pay attention to the issues of efficiency, environmental protection and sustainable development	0.78(p < 0.001***)	0.84(p < 0.001***)
	Meet the needs of an inclusive and diverse society	0.78(p < 0.001***)	0.83(p < 0.001)***)

Note: ^*P < 0.10. ^**P < 0.05. ^***P < 0.01 Pearson correlation coefficients are reported in the table

Validity

This study assessed questionnaire validity to determine the appropriateness of item design. Firstly, exploratory factor analysis was carried out, and it can be seen from Table 3 that the KMO values of the importance for professional growth and the satisfaction with teaching were 0.955 and 0.976 respectively. The validity of the questionnaire data was relatively high through the Bartlett spherical test (p < 0.01).

Table 3.

KMO and Bartlett spherical test

		Importance for professional growth	Satisfaction with teaching
KMO value		0.95	0.97
Bartlett spherical test	Approximate chi-square	18799.56	26661.87
	df	820	820
	P-value	< 0.001***	< 0.001***

Note: ^*P < 0.10. ^**P < 0.05. ^***P < 0.01

Tables 4 and 5 show factor loading of each item of both importance for professional growth and satisfaction with teaching. Using Principal Component Analysis (PCA) with varimax rotation, we retained four factors based on eigenvalues > 1 and alignment with the original questionnaire dimensions. We assigned indicators to different factors according to factor loading coefficient values. When the loading coefficient of an item on a factor reached 0.40 and was significantly higher than its load on other factors, the item was classified into that factor. Based on theoretical connotations and research objectives, we prioritize factors with higher conceptual fit for items with cross loading. In the questionnaire of the importance for professional growth, “Mathematical knowledge of computing and description”, “Big data”, “Artificial intelligence”, “drug economic management, pharmaceutical management”, “relationship between people and society, and the background of pharmaceutical activities” should be included in common factor 3. After considering the background and meaning of the comprehensive indicators, these items are still classified into the original dimensions for analysis.

Table 4.

The factor loading coefficient in questionnaire of the importance for professional growth

	Factor1	Factor2	Factor3	Factor4
Computational and descriptive mathematical knowledge	-0.05	0.55	0.31	0.21
Pharmaceutical-related chemistry knowledge	0.07	0.21	0.44	0.35
Knowledge of new equipment in pharmaceuticals	0.12	0.31	0.37	0.45
Knowledge of new pharmaceutical processes and new technologies	0.13	0.19	0.54	0.35
Knowledge of drug design, synthesis, formulation, and translation	0.19	0.10	0.55	0.20
Biological knowledge of drugs	0.28	0.26	0.45	0.05
Big data	0.22	0.65	0.23	0.00
AI (artificial intelligence)	0.19	0.66	0.21	0.04
Economic management of drugs	0.05	0.75	0.02	0.27
Relationships between people and society	0.12	0.63	0.05	0.25
Apply mathematics and physics to logical reasoning and analysis	0.10	0.39	0.51	0.23
Use chemistry for scientific analysis and judgment	0.19	0.21	0.65	0.13
Apply pharmacy for in-depth understanding and scientific research	0.27	0.02	0.70	0.08
Use biology for identification and application	0.32	0.06	0.66	0.07
Use engineering knowledge to conduct systematic analysis and rationality demonstration	0.20	0.17	0.52	0.24
Data skills such as data collection, refining, and processing (partial software)	0.37	0.49	0.34	-0.08
Use of modern analytical and testing instruments, qualitative and quantitative analysis (partial hardware)	0.37	0.52	0.29	-0.05
Use new technologies, new tools	0.47	0.49	0.20	-0.02
Research and judgment skills, risk assessment skills	0.47	0.41	0.16	0.24
Systems thinking (full cycle, full process control)	0.50	0.39	0.16	0.29
Grasp the rules of project operation	0.45	0.42	0.13	0.33
Optimize the economic decisions of your engineering projects	0.35	0.52	0.09	0.33
Time & Resource Management (Project-based)	0.46	0.36	0.25	0.26
Forward-looking, strategic thinking and insight into the pharmaceutical industry	0.55	0.20	0.30	0.10
Strong willpower to face the unknown	0.54	0.27	0.20	0.08
User thinking with market ability	0.38	0.38	0.07	0.42
Communication skills	0.57	0.34	0.12	0.23
Teamwork (cross-border integration)	0.61	0.30	0.15	0.17
Leadership	0.44	0.45	0.01	0.36
Global competence	0.53	0.29	0.17	0.31
Curiosity, continuous lifelong learning	0.70	0.08	0.24	0.12
Metacognition, self-knowledge, self-reflection	0.66	0.14	0.24	0.22
Knowledge transfer and problem-solving skills in complex contexts	0.60	0.11	0.30	0.21
Ability to innovate, with a strong desire to break through the stuck neck technology	0.70	0.08	0.21	0.17
Entrepreneurship and entrepreneurial ability	0.62	0.13	0.16	0.29
cherish the greatness of the country	0.57	-0.01	0.15	0.36
Altruism, dedication	0.42	0.15	0.12	0.60
Pharmaceutical Engineering Ethics and Norms	0.44	0.01	0.30	0.47
Undertake health, safety, legal and cultural social responsibilities	0.27	0.14	0.28	0.68
Pay attention to the issues of efficiency, environmental protection and sustainable development	0.31	0.16	0.28	0.62
Meet the needs of an inclusive and diverse society	0.31	0.19	0.24	0.61

Note: The eigenvalues of the first four factors extracted by principal component analysis are all greater than 1, and the cumulative variance contribution rate is 49.91%

Table 5.

The factor loading coefficient of each Indicator in questionnaire of the satisfaction with teaching

	Factor1	Factor2	Factor3	Factor4
Computational and descriptive mathematical knowledge	0.51	0.04	0.46	0.20
Pharmaceutical-related chemistry knowledge	0.04	0.20	0.72	0.16
Knowledge of new equipment in pharmaceuticals	0.28	0.26	0.58	0.20
Knowledge of new pharmaceutical processes and new technologies	0.26	0.22	0.66	0.16
Knowledge of drug design, synthesis, formulation, and translation	0.21	0.22	0.62	0.24
Biological knowledge of drugs	0.28	0.24	0.56	0.15
Big data	0.78	0.23	0.15	0.12
AI (artificial intelligence)	0.79	0.24	0.10	0.14
Economic management of drugs	0.77	0.27	0.10	0.07
Relationships between people and society	0.66	0.17	0.23	0.18
Apply mathematics and physics to logical reasoning and analysis	0.49	0.15	0.46	0.20
Use chemistry for scientific analysis and judgment	0.23	0.23	0.59	0.28
Apply pharmacy for in-depth understanding and scientific research	0.17	0.19	0.63	0.31
Use biology for identification and application	0.21	0.21	0.64	0.24
Use engineering knowledge to conduct systematic analysis and rationality demonstration	0.40	0.24	0.47	0.28
Data skills such as data collection, refining, and processing (partial software)	0.53	0.42	0.29	0.15
Use of modern analytical and testing instruments, qualitative and quantitative analysis (partial hardware)	0.46	0.36	0.40	0.05
Use new technologies, new tools	0.57	0.40	0.34	0.06
Research and judgment skills, risk assessment skills	0.70	0.34	0.21	0.16
Systems thinking (full cycle, full process control)	0.65	0.32	0.26	0.19
Grasp the rules of project operation	0.63	0.29	0.25	0.21
Optimize the economic decisions of your engineering projects	0.62	0.37	0.24	0.14
Time & Resource Management (Project-based)	0.47	0.54	0.22	0.22
Forward-looking, strategic thinking and insight into the pharmaceutical industry	0.30	0.63	0.31	0.14
Strong willpower to face the unknown	0.35	0.61	0.30	0.16
User thinking with market ability	0.43	0.63	0.15	0.21
Communication skills	0.24	0.65	0.26	0.22
Teamwork (cross-border integration)	0.20	0.63	0.31	0.24
Leadership	0.30	0.65	0.25	0.23
Global competence	0.38	0.64	0.16	0.24
Curiosity, continuous lifelong learning	0.22	0.65	0.19	0.33
Metacognition, self-knowledge, self-reflection	0.23	0.65	0.24	0.36
Knowledge transfer and problem-solving skills in complex contexts	0.24	0.63	0.24	0.34
Ability to innovate, with a strong desire to break through the stuck neck technology	0.32	0.61	0.20	0.39
Entrepreneurship and entrepreneurial ability	0.34	0.59	0.21	0.35
cherish the greatness of the country	0.03	0.30	0.41	0.56
Altruism, dedication	0.17	0.32	0.31	0.66
Pharmaceutical Engineering Ethics and Norms	0.10	0.31	0.32	0.67
Undertake health, safety, legal and cultural social responsibilities	0.21	0.28	0.29	0.70
Pay attention to the issues of efficiency, environmental protection and sustainable development	0.27	0.30	0.24	0.71
Meet the needs of an inclusive and diverse society	0.22	0.29	0.24	0.72

Note: The eigenvalues of the first four factors extracted by principal component analysis are all greater than 1, and the cumulative variance contribution rate is 60.51%

To ensure the validity of the questionnaire, we also carried out confirmatory factor analysis. According to the four dimensions divided by the original questionnaire, we found that the factor loading coefficients of each item exceeded 0.6, and the measured variables passed the significance test (P < 0.05), which was considered to have sufficient variance explanation rate to show that all variables could be displayed on the same factor.

The obtained data were analyzed according to the four dimensions and the results showed that the RMSEA = 0.07, CFI = 0.77, NFI = 0.77 in the questionnaire of the importance for professional growth, the RMSEA = 0.07, CFI = 0.86, NFI = 0.84 in the questionnaire of the satisfaction with teaching (Table 6). The confirmatory factor analysis showed that the questionnaire model was well adapted (index greater than 0.8). Combined with the results of the previous validity analysis, the questionnaire was valid.

Table 6.

Confirmatory factor analysis model fit metrics

Fit metrics	Importance for professional growth	Satisfaction with teaching
	Indicator values	Indicator values
GFI	0.77	0.84
CFI	0.80	0.86
NFI	0.77	0.84
RMSEA	0.07	0.07

Data collection

This study selected a pharmaceutical university as its research site, targeting senior undergraduates (years 2–3) graduate students, and in-service students (post-master’s professionals pursuing continuing education). Senior undergraduates were included because their completion of ≥ 1 years of study enabled informed perspectives on pharmacy program efficacy. According to the sample size calculation formula , we take α = 0.01, P = 0.5, E = 0.05, the minimum sample size required for this survey is 664. Considering the recovery rate of the questionnaire and the inevitable non-response phenomenon in the sampling survey, the sample size needs to be expanded to 863. The survey was conducted in June, 2024. The process selected 31 classes of second- and third-year students in the School of Pharmacy utilizing a cluster sampling approach. We selected seven pharmacy-related majors: Traditional Chinese Pharmacy, Pharmaceutical Engineering, Traditional Chinese Pharmaceutical Manufacturing, Outstanding Engineer Education and Training Program, Cosmetics, Biopharmaceutical, and Pharmacy. These seven majors strictly adhere to the classification standards established in China’s Ministry of Education’s “Catalogue of Undergraduate Majors in Ordinary Colleges and Universities (2020 Edition)”, and all belong to the major category of pharmacy majors in the second-level professional direction under the first-level discipline of pharmacy. Covering 50% of China’s 14 pharmacy-related undergraduate majors, the selected programs represent both traditional and emerging pharmaceutical specializations.

First, according to the different professional directions, the target student group is divided into several “layers”, and then the class is used as the basic sampling unit. For “layers” with less than 3 classes (≤ 3 classes), all classes in the layer are invited to participate in the survey. For “layers” with more than 3 classes (> 3 classes) in the major, half of the classes are randomly selected from the layer, and all students in the selected classes need to participate in the survey. The final undergraduate sample is made up of students from all selected classes.

Students from these seven majors voluntarily completed paper-based questionnaires, which were uniformly distributed and collected by the research team, with completion times ranging between 8 and 10 min. From a total of 858 distributed questionnaires, researchers received 784 returns (73 remained unsubmitted) with 60 questionnaires incomplete. A total of 724 valid questionnaires were collected. Three independent graduate teams performed double-data entry with cross-verification, ensuring data integrity.

In addition, the transfer of pharmaceutical majors from undergraduate to graduate education has become a global consensus and basic concept for the cultivation of pharmaceutical talents. Therefore, an online survey with potential 300 respondents was conducted in June, 2024, over a three-week period, facilitated participation from undergraduate students to graduate students and in-service students. A total of 196 people returned the questionnaire with 195 being valid. The response rate was 99.48%.

Data analysis

Data processing

To ensure maximum accuracy and reliability, the research processed all collected data according to the following procedures.

We first eliminated responses with logical inconsistencies or missing values. Additionally, online submissions completed in under 60 s were excluded to avoid careless responses. Finally, cross-validation by three independent teams confirmed accurate data entry, guaranteeing a reliable data set for analysis.

In total, the questionnaire received 919 valid responses, distributed across education levels as follows: 724 undergraduates (78.78%), 167 master’s-level students (18.17%), and 28 doctoral candidates (3.05%) (Table 7). The questionnaire response rate reached 87.19%, meeting the required standard.

Table 7.

Baseline characteristics of the respondents

Indicators	Characteristics	Undergraduates (N = 724)	Master’s Students (N = 167)	Doctoral Students (N = 28)
Gender	Male	311 (42.96%)	61 (36.53%)	19 (67.86%)
	Female	413 (57.04%)	106 (63.47%)	9 (32.14%)
Year of Study	1st Year		48 (28.75%)	14 (50.00%)
	2nd Year	382 (52.76%)	51 (29.94%)	10 (35.71%)
	3rd Year	342 (47.24%)	30 (18.56%)	4 (14.29%)
	4th Year
Work Experience	In-service students		38 (22.75%)
	Yes	455 (62.85%)	105 (62.87%)	16 (57.14%)
	No	269 (37.15%)	62 (37.13%)	12 (42.86%)

Data analysis plan

Data entry was performed using Excel 2021, with subsequent analyses conducted in R and SPSS. Descriptive statistics computed mean ± SD scores for “importance for professional growth” and “satisfaction with teaching” across all competency dimensions. Quantitative data normality was assessed via Shapiro-Wilk tests and skewness coefficients, supplemented by histogram visualization. The Pearson correlation coefficient was used to analyze the correlation of core competencies’ “importance for professional growth” and “satisfaction with teaching”. We applied one-way ANOVA analysis to test how education level might affect students’ perceptions of which knowledge, skills, abilities, and values were most important for professional growth, as well as their satisfaction with teaching. Prior to analysis, a test for normality was performed, followed by a test for homogeneity of variance and a post-hoc multiple comparison validation using Tukey’s HSD method, which included multiple comparison correction. For deficiency of identification (binary 0–1 variables), chi-square tests detected significant differences in self-perceived competency gaps across academic stages, with P < 0.1 considered statistically significant in this exploratory analysis.

Results

Overall assessment of core competencies in pharmaceutical students

Evaluation of core knowledge

Table 8 shows students’ evaluation of 10 kinds of knowledge in pharmacy. The three most important types of knowledge for professional growth of the pharmacy students were “drug-related chemistry knowledge” (mean = 4.56, rate = 86.29%), “Knowledge of Drug Design, Formulation, Translational Medicine, and Application” (mean = 4.44, rate = 81.61%) and “Knowledge of Advanced Pharmaceutical Processes and Technologies” (mean = 4.38, rate = 81.61%). This may be because pharmaceutical knowledge is the basis for ensuring production quality, and the core of new drug creation, which runs through the whole life cycle. Pharmaceutical students believe that this knowledge is fundamental to their future career development. However, the interdisciplinary nature of modern pharmacy necessitates greater emphasis on emerging domains like “artificial intelligence” and “pharmaceutical economics”, where recognition of their strategic value remains underdeveloped.

Table 8.

Evaluation of importance for professional growth and satisfaction with teaching of core competencies in knowledge dimension (N = 919)

Importance for professional growth	Mean (SD)	Rate(%)	Satisfaction with teaching	Mean (SD)	Rate(%)
Pharmaceutical Chemistry Knowledge	4.56 (0.58)	95.43%	Pharmaceutical Chemistry Knowledge	4.28 (0.70)	86.29%
Drug Design, Formulation, Translational Medicine, and Application Knowledge	4.44 (0.67)	90.75%	Drug Design, Formulation, Translational Medicine, and Application Knowledge	4.22 (0.70)	81.61%
Advanced Pharmaceutical Processes and Technologies	4.38 (0.67)	90.64%	Advanced Pharmaceutical Processes and Technologies	4.18 (0.75)	81.61%
Mathematical and Statistical Knowledge	4.36 (0.72)	87.81%	Mathematical and Statistical Knowledge	4.13 (0.76)	80.20%
Pharmaceutical Biology Knowledge	4.32 (0.70)	87.27%	Pharmaceutical Biology Knowledge	4.12 (0.82)	78.24%
New Pharmaceutical Equipment	4.28 (0.73)	86.62%	New Pharmaceutical Equipment	4.09 (0.78)	76.82%
Big Data	4.08 (0.80)	76.39%	Big Data	3.87 (0.94)	66.05%
Artificial Intelligence (AI)	4.00 (0.84)	72.14%	Artificial Intelligence (AI)	3.77 (0.97)	62.57%
Social and Human Relations Knowledge	3.92 (0.95)	69.10%	Social and Human Relations Knowledge	3.74 (1.03)	60.28%
Pharmaceutical Economics and Management	3.77 (0.99)	63.44%	Pharmaceutical Economics and Management	3.73 (1.02)	59.19%

Note: Rate refers to the proportion of the number of samples with respondent scores of “4” and “5” in the total number of samples, the same below

The evaluation of importance and satisfaction is based on the likert5 scale, and 5 indicate the deepest degree, the same below

SD: Standard Deviation, the same below

Further, Fig. 1 shows the deficiencies in ten core knowledge areas of pharmaceutical students. In the questionnaire, we designed multiple-choice questions to require students to choose the 3 knowledge items they lacked the most, and the table counted the probability of each option being selected (the same below). From the survey, we can see that “Drug Design, Formulation, Translational Medicine, and Application Knowledge” (40.8%), “Artificial Intelligence” (39.28%), and “Big data” (31.01%) are what they lack the most. This result means that pharmaceutical education is disconnected from the needs of practice which cannot meet the pharmaceutical industry’s demand for compound and applied talents. On the other hand, pharmaceutical development has entered a new stage of “AI-driven”. Students realize that there is a sharp contradiction between the iterative speed of artificial intelligence technology and the lag of education, and urgently expect to improve AI knowledge reserve.

Fig. 1.

Analysis of Students’ Deficiencies in 10 Core Knowledge Areas of Pharmaceutical Core Competencies

Evaluation of core skills

Students’ assessments of 12 essential skills in pharmaceutical education are presented in Table 9. “Drug understanding and evaluation” were rated the most important for professional growth, receiving the highest mean score of 4.38 (Rate = 87.70%). “Chemical analysis and decision-making” also gained high ratings, achieving a mean importance score of 4.35 (Rate = 89.45%) and “Biological Identification and Application” score of 4.35 (Rate = 86.83%). This shows that the education of these skills in schools has formed a positive closed loop between teaching design, practical value and vocational demand, which is a successful practice of integration of production and education. The mature teaching system guarantees the quality of skills training of pharmaceutical students. On the contrary, students do not pay much attention to the skills such as “Risk Assessment and Judgment”, which indicates that schools fail to attach importance to the educational mission of “ensuring drug safety”, “risk assessment” needs to be embedded in the student training program in the future.

Table 9.

Evaluation of importance for professional growth and satisfaction with teaching of core competencies in skill dimension (N = 919)

	Importance for professional Growth	Mean (SD)	Rate(%)	Satisfaction with Teaching	Mean (SD)	Rate(%)
Problem Identification and Analysis	Chemical Analysis and Decision-Making	4.38 (0.71)	87.70%	Chemical Analysis and Decision-Making	4.25 (0.74)	84.87%
	Drug Understanding and Evaluation	4.35 (0.69)	89.45%	Drug Understanding and Evaluation	4.23 (0.74)	83.13%
	Biological Identification and Application	4.35 (0.72)	86.83%	Biological Identification and Application	4.21 (0.74)	86.83%
	System Design and Validation	4.32 (0.74)	88.57%	System Design and Validation	4.12 (0.77)	78.13%
	Logical Reasoning Utilizing Mathematics and Physics	4.24 (0.78)	84.11%	Logical Reasoning Utilizing Mathematics and Physics	4.12 (0.77)	79.65%
Application Tool	Use of New Technologies and Tools	4.29 (0.72)	85.75%	Hardware Skills (Modern Analytical Instruments)	4.06 (0.83)	75.41%
	Software Skills (Data Collection and Analysis)	4.26 (0.74)	85.42%	Use of New Technologies and Tools	4.00 (0.86)	72.03%
	Hardware Skills (Modern Analytical Instruments)	4.25 (0.74)	85.42%	Software Skills (Data Collection and Analysis)	3.97 (0.85)	71.16%
Project Management	Project Management Rule	4.25 (0.78)	84.66%	System Thinking (Full Lifecycle Management)	3.97 (0.88)	70.29%
	Risk Assessment and Judgment	4.24 (0.78)	82.92%	Project Management Rule	3.97 (0.88)	70.84%
	System Thinking (Full Lifecycle Management)	4.23 (0.75)	85.53%	Risk Assessment and Judgment	3.93 (0.90)	68.12%
	Economic Decision Optimization	4.15 (0.80)	80.41%	Economic Decision Optimization	3.91 (0.92)	67.36%

Several skill domains exhibited significant deficiencies, notwithstanding the generally positive evaluations. A portion of students (41.24%) acknowledged deficiencies in their “logical reasoning abilities utilizing mathematical and physical principles” (Fig. 2), higher than “systematic thinking” and “Drug Understanding and Evaluation”. The main reason for this phenomenon lies in the structural imbalances of educational supply. On the one hand, the colleges mainly focus on the cultivation of pharmaceutical skills, and the class hours for mathematics and physics courses are relatively short, on the other hand, most teachers possess chemistry and biology backgrounds and lack professional expertise in mathematical applications. It has become the biggest obstacle factor restricting the improvement of the overall skill level of pharmaceutical students.

Fig. 2.

Analysis of Students’ Deficiencies in 12 Core Skills of Pharmaceutical Core Competencies

Evaluation of core abilities

Table 10 summarizes student evaluations across 13 essential abilities. From the analysis of the three dimensions of ability, in terms of individual internal ability, “Strategic and Forward-Thinking Insight into the Pharmaceutical Industry” is the most important for students(mean = 4.38), and it is also the best ability for the satisfaction with teaching (rate = 88.9%). This is because the pharmaceutical research and development industry has the characteristics of “long cycle, high investment, and high risk”. In response to the high complexity and rapid changes in the pharmaceutical industry, forward thinking and strategic thinking have become the core survival skills and competitiveness of pharmaceutical students. In terms of interpersonal skills, 87.49% of students believed that “Team Collaboration (Cross-Disciplinary Integration)” was important. This may be because the inherent complexity of pharmaceutical research and production requires interdisciplinary knowledge integration, and the operation of the pharmaceutical industry chain cannot be separated from efficient team collaboration. For sustainable development abilities, the students’ satisfaction rate with the teaching of various abilities is relatively low, which reveals that there are structural contradictions and challenges in the education system of pharmaceutical universities in China.

Table 10.

Evaluation of importance for professional growth and satisfaction with teaching of core competencies in ability dimension (N = 919)

	Importance for professional Growth	Mean (SD)	Rate(%)	Satisfaction with Teaching	Mean (SD)	Rate(%)
Individual Internal Ability	Strategic and Forward-Thinking Insight into the Pharmaceutical Industry	4.38 (0.72)	88.90%	Strategic and Forward-Thinking Insight into the Pharmaceutical Industry	4.08 (0.82)	75.30%
	Resilience in Facing the Unknown	4.32 (0.74)	87.60%	Resilience in Facing the Unknown	4.05 (0.82)	74.21%
	User-Centered Thinking	4.22 (0.80)	84.22%	Resource and Time Management in Projects	4.04 (0.85)	73.78%
	Resource and Time Management in Projects	4.22 (0.76)	82.26%	User-Centered Thinking	3.96 (0.89)	69.10%
Interpersonal Skills	Team Collaboration (Cross-Disciplinary Integration)	4.30 (0.72)	87.49%	Communication Skills	4.07 (0.82)	75.63%
	Communication Skills	4.29 (0.74)	86.51%	Team Collaboration (Cross-Disciplinary Integration)	4.04 (0.83)	74.21%
	Global Competence	4.27 (0.75)	85.75%	Global Competence	4.01 (0.86)	74.65%
	Leadership	4.13 (0.79)	79.87%	Leadership	3.96 (0.84)	68.88%
Sustainable Development Skills	Innovation Capability: Strong desire for technological innovation	4.39 (0.73)	88.79%	Complex Problem-Solving and Knowledge Transfer in Challenging Contexts	4.11 (0.82)	77.58%
	Complex Problem-Solving and Knowledge Transfer in Challenging Contexts	4.37 (0.72)	88.25%	Innovation Capability: Strong desire for technological innovation	4.08 (0.82)	75.30%
	Curiosity and Lifelong Learning Ability	4.36 (0.74)	87.49%	Entrepreneurial Spirit and Capability	4.07 (0.85)	76.06%
	Entrepreneurial Spirit and Capability	4.34 (0.76)	84.66%	Curiosity and Lifelong Learning Ability	4.07 (0.81)	76.06%
	Metacognition: Self-awareness and Reflection	4.33 (0.72)	87.70%	Metacognition: Self-awareness and Reflection	4.06 (0.82)	75.73%

An analysis of gaps in pharmacy students’ core competencies indicates critical findings, as depicted in Fig. 3. “Strategic and Forward-Thinking Insight into the Pharmaceutical Industry” (37.43%) and “Global Competence” (29.05%) occupied the top deficiency positions, with their deficiency rates significantly outpacing other abilities. This shows that the reform and fierce competition environment of the pharmaceutical industry, pharmaceutical students realize their lack of ability to judge the development direction of the industry, and expect to keep vigilant and learn at all times, reflecting the higher pursuit of pharmaceutical students for their own role and the future development of the industry in the new era.

Fig. 3.

Analysis of Students’ Deficiencies in 13 Core Abilities of Pharmaceutical Core Competencies

Evaluation of core values

Table 11 shows the evaluation of 6 core values in pharmacy by students. On the one hand, students have a high level of satisfaction with the importance of values and major teaching. They believe that the most important value for professional growth is “ethical and moral norms” (mean = 4.43); And the satisfaction rate with teaching of this value system also reached 82.37%, indicating that the school has successfully shaped the values of students’ professional norms, the importance students attach to this value is to have a clear understanding of the essence of “pharmacy is not an ordinary commodity.“; On the other hand, there is a partial imbalance in students’ understanding of values in the pharmaceutical and social dimensions: about 90% of students believe that cultivating the value of “meeting the needs of an inclusive and diverse society” is crucial, but nearly 20% of the surveyed students believe that their profession does not adequately shape this value, which means there is a disconnect between the pharmaceutical education system of universities and the needs of social reality, pharmaceutical education does not pay enough attention to the core values such as social health equity.

Table 11.

Evaluation of importance for professional growth and satisfaction with teaching of core competencies in value Dimension(N = 919)

	Importance for Professional Growth	Mean (SD)	Rate (%)	Satisfaction with Teaching	Mean (SD)	Rate (%)
Professional norms	Ethics and Professional Norms	4.43 (0.69)	90.42%	National Responsibility	4.28 (0.76)	83.03%
	National Responsibility	4.42 (0.75)	87.70%	Ethics and Professional Norms	4.23 (0.76)	82.37%
	Dedication and Commitment	4.34 (0.77)	85.96%	Dedication and Commitment	4.22 (0.77)	81.83%
Pharmacy and Society	Addressing Inclusive and Diverse Social Needs	4.39 (0.71)	89.77%	Responsibility for Health, Safety, Legal, and Cultural Issues	4.23 (0.76)	83.79%
	Emphasis on Efficiency, Environmental Protection, and Sustainability Development	4.38 (0.69)	89.45%	Emphasis on Efficiency, Environmental Protection, and Sustainability Development	4.21 (0.78)	81.61%
	Responsibility for Health, Safety, Legal, and Cultural Issues	4.37 (0.73)	88.36%	Addressing Inclusive and Diverse Social Needs	4.18 (0.79)	80.52%

Figure 4 shows the lack of values among pharmaceutical students. Especially the value of “understanding inclusive and diverse social needs”, students believe that this value is important for professional growth (mean = 4.39, rate = 89.77%), but the satisfaction of professional professors ranks last (mean = 4.18, standard deviation 0.79). At the same time, 54.2% of students believe that they lack this value, indicating that students lack patient-centered humanistic training which deserves attention from the school.

Fig. 4.

Analysis of Students’ Deficiencies in 6 Core Values of Pharmaceutical Core Competencies

The descriptive analysis results of the core competencies in the four dimensions of knowledge, skills, abilities and values show that students attach high importance to core competencies and it is also relatively high in satisfaction with teaching. Conversely, competencies perceived as less important show correspondingly lower teaching satisfaction, with statistically significant correlations observed in knowledge and skills dimensions. Surprisingly, students have high evaluation of certain core competencies, but our study shows that these students sometimes are currently undertrained in these core competencies, such as the knowledge “Drug Design, Formulation, Translational Medicine, and Application Knowledge”, which requires deeper analysis through qualitative investigation.

Analysis of the difference between importance for professional growth and satisfaction with teaching of core competencies

In order to explore whether there is correlation between the importance for professional growth and satisfaction with teaching, as well as the difference between importance for professional growth and satisfaction with teaching of core competencies, the T-test of paired samples was conducted to explore the difference.

Value dimension

T-test analysis comparing core competency importance recognition and teaching satisfaction revealed statistically significant differences between these variables(Tables 12, 13, 14 and 15). This indicates that students’ recognition of the importance of core competency and evaluation of teaching satisfaction are relatively independent, except for some items such as “the relationship between human and society, the background of pharmaceutical activities” and “drug economic management, pharmaceutical affairs management”.

Table 12.

Analysis of the difference between importance for professional growth and satisfaction with teaching in knowledge dimension

	Correlation Coefficient	Cohen’s d	t(df)	p-value
Pharmaceutical-related chemistry knowledge	0.17	0.34	10.35(918)	< 0.001
Knowledge of drug design, synthesis, formulation, and translation	0.23	0.24	7.43(918)	< 0.001
Knowledge of new pharmaceutical processes and new technologies	0.28	0.24	7.27(918)	< 0.001
Computational and descriptive mathematical knowledge	0.27	0.30	9.12(918)	< 0.001
Biological knowledge of drugs	0.23	0.22	6.59(918)	< 0.001
Knowledge of new equipment in pharmaceuticals	0.26	0.17	5.26(918)	< 0.001
Big Data	0.26	0.28	8.50(918)	< 0.001
AI (artificial intelligence)	0.22	0.23	6.84(918)	< 0.001
Relationships between people and society	0.38	0.04	1.23(918)	0.22
Economic management of drugs	0.47	0.04	1.15(918)	0.25

Table 13.

Analysis of the difference between importance for professional growth and satisfaction with teaching in skill dimension (N = 919)

	Correlation Coefficient	Cohen’s d	t(df)	p-value
Apply pharmacy for in-depth understanding and scientific research	0.19	0.16	4.94(918)	< 0.001
Use chemistry for scientific analysis and judgment	0.18	0.12	3.51(918)	< 0.001
Use biology for identification and application	0.23	0.15	4.47(918)	< 0.001
Use engineering knowledge to conduct systematic analysis and rationality demonstration	0.24	0.21	6.43(918)	< 0.001
Use new technologies, new tools	0.21	0.29	8.67(918)	< 0.001
Data skills such as data collection, refining, and processing (partial software)	0.19	0.29	8.63(918)	< 0.001
Grasp the rules of project operation	0.26	0.28	8.35(918)	< 0.001
Use of modern analytical and testing instruments, qualitative and quantitative analysis (partial hardware)	0.24	0.19	5.92(918)	< 0.001
Research and judgment skills, risk assessment skills	0.21	0.29	8.93(918)	< 0.001
Apply mathematics and physics to logical reasoning and analysis	0.28	0.13	3.82(918)	< 0.001
Systems thinking (full cycle, full process control)	0.28	0.27	8.12(918)	< 0.001
Optimize the economic decisions of your engineering projects	0.28	0.22	6.78(918)	< 0.001

Table 14.

Analysis of the difference between importance for professional growth and satisfaction with teaching in ability dimension (N = 919)

	Correlation Coefficient	Cohen’s d	t(df)	p-value
Ability to innovate, with a strong desire to break through the stuck neck technology	0.18	0.28	8.34(918)	< 0.001
Forward-looking, strategic thinking and insight into the pharmaceutical industry	0.19	0.31	9.33(918)	< 0.001
Knowledge transfer and problem-solving skills in complex contexts	0.23	0.28	8.36(918)	< 0.001
Curiosity, continuous lifelong learning	0.20	0.29	8.95(918)	< 0.001
Entrepreneurship and entrepreneurial ability	0.24	0.27	8.17(918)	< 0.001
Metacognition, self-knowledge, self-reflection	0.32	0.31	9.31(918)	< 0.001
Strong willpower to face the unknown	0.25	0.28	8.52(918)	< 0.001
Teamwork (cross-border integration)	0.19	0.26	7.78(918)	< 0.001
Communication skills	0.20	0.22	6.73(918)	< 0.001
Global competence	0.23	0.26	7.97(918)	< 0.001
User thinking with market ability	0.30	0.18	5.34(918)	< 0.001
Time & Resource Management (Project-based)	0.23	0.27	8.07(918)	< 0.001
Leadership	0.26	0.18	5.32(918)	< 0.001

Table 15.

Analysis of the difference between importance for professional growth and satisfaction with teaching in value dimension (N = 919)

	Correlation Coefficient	Cohen’s d	t(df)	p-value
Ethics and Norms	0.33	0.24	7.24(918)	< 0.001
cherish the greatness of the country	0.28	0.15	4.65(918)	< 0.001
Meet the needs of an inclusive and diverse society	0.30	0.23	7.02(918)	< 0.001
Pay attention to the issues of efficiency, environmental protection and sustainable development	0.39	0.22	6.57(918)	< 0.001
Undertake health, safety, legal and cultural social responsibilities	0.32	0.17	5.04(918)	< 0.001
Altruism, dedication	0.33	0.13	3.88(918)	< 0.001

Differences in core competencies evaluations across education levels

Pearson correlation analysis

Prior to difference analysis, Pearson correlation analyses were conducted between core competency importance perceptions and teaching satisfaction evaluations, with results detailed in Table 16. There is a strong correlation between students’ education level and the evaluation of the importance of core competencies, the satisfaction with teaching, and there is also a strong correlation between different core competencies, the importance of core competencies and the satisfaction with teaching.

Table 16.

Pearson correlation analysis (N = 919)

	Grade	m1	m2	m3	m4	n1	n2	n3	n4
Grade	1.00
m1	-0.17***	1.00
m2	-0.03	0.27***	1.00
m3	-0.06*	0.24***	0.35***	1.00
m4	-0.08**	0.31***	0.32***	0.45***	1.00
n1	0.16***	0.14***	0.02	0.05	0.10***	1.00
n2	0.13***	0.14***	0.11***	0.09***	0.12***	0.54***	1.00
n3	0.08**	0.19***	0.15***	0.12***	0.14***	0.53***	0.55***	1.00
n4	-0.02	0.17***	0.17***	0.21***	0.25***	0.30***	0.40***	0.48***	1.00

Note: m1 = most important knowledge for growth, m2 = most important skill for growth, m3 = most important ability for growth, m4 = most important value for growth

n1 = most unsatisfactory knowledge for professional teaching, n2 = most unsatisfactory skill for professional teaching, n3 = most unsatisfactory ability for professional teaching, n4 = most unsatisfactory value for professional teaching

^*P < 0.10. ^**P < 0.05. ^***P < 0.01

Analysis of core competencies difference among students in different education level

According to Pearson’s correlation analysis, there may be differences of students’ core competencies at different education levels due to the influence of learning experience. This study stratified samples into undergraduate, master’s, and doctoral cohorts. One-way ANOVA examined how academic progression influences pharmacy students’ core competency importance perceptions and teaching satisfaction, with Tukey’s HSD post-hoc tests identifying inter-group differences (Table 17).

Table 17.

Results of variance analysis of the most important and least satisfactory core competencies in different education levels

	Group a Mean(SD)	Group b Mean(SD)	Group c Mean(SD)	F value	P value	HSD post-hoc	95%confidence interval
							lower limit	upper limit
Importance: Pharmaceutical Chemistry Knowledge	4.62 (0.57)	4.37 (0.59)	4.35 (0.62)	14.84***	< 0.001	a > b, p < 0.001*** a > c, p = 0.02**	0.14 0.00	0.37 0.52
Teaching Satisfaction: Pharmaceutical Economics and Management Knowledge	3.82 (0.99)	4.08 (0.68)	4.07 (0.60)	13.73***	< 0.001	b > a, p < 0.001*** b > c, p = 0.94	0.23 -0.41	0.64 0.55
Importance: Drug Understanding and Evaluation	4.39 (0.74)	4.35 (0.62)	4.29 (0.53)	0.51	0.60	b > a, p = 0.76 b > c, p = 0.91	-0.19 -0.28	0.10 0.40
Teaching Satisfaction: Economic Decision Optimization	3.84 (0.98)	4.19 (0.62)	4.11 (0.63)	10.15***	< 0.001	b > a, p < 0.001*** b > c, p = 0.91	0.16 -0.36	0.53 0.52
Importance: Innovation Capability	4.41 (0.77)	4.33 (0.56)	4.21 (0.50)	1.63	0.20	a > b, p = 0.41 a > c, p = 0.35	-0.17 -0.13	0.23 0.52
Teaching Satisfaction: User-Centered Thinking	3.91 (0.94)	4.12 (0.63)	4.07 (0.66)	3.96**	0.02	b > a, p = 0.02** b > c, p = 0.96	0.03 -0.38	0.39 0.47
Importance: Ethics and Professional Norms	4.45 (0.72)	4.37 (0.59)	4.18 (0.55)	2.98*	0.05	a > b, p = 0.30 a > c, p = 0.10*	-0.05 -0.04	0.23 0.59
Teaching Satisfaction: Addressing Diverse and Inclusive Social Needs	4.19 (0.83)	4.13 (0.64)	4.18 (0.55)	0.38	0.69	a > b, p = 0.66 a > c, p = 0.99	-0.10 -0.34	0.22 0.37

A = Undergraduate, B = Master’s Student, C = Doctoral Student

^*P < 0.10. ^**P < 0.05. ^***P < 0.01

In terms of knowledge, undergraduates’ awareness of the importance of “Pharmaceutical Chemistry Knowledge” was significantly higher than that of master’s and doctoral students, with an F-statistic of 14.84, reaching the significance level test of 1% (P < 0.001) and HSD post-hoc comparison test. As for the results of dissatisfaction of “Pharmaceutical Economics and Management Knowledge”, master students’ was significantly higher than that of undergraduates, which is significant at the 1% level (P < 0.001). This shows that undergraduates pay more attention to the cultivation of basic knowledge of pharmacy, while graduate students have lower satisfaction with course teaching.

In the technical dimension, undergraduates’ awareness of the importance of “Drug Understanding and Evaluation” as the most important skill in growth (mean = 4.39) is greater than that of master’s students (mean = 4.25) and doctoral students (4.29), but this difference does not pass the significance test; and regarding the most unsatisfactory skill currently taught by “Economic Decision Optimization”, the Tukey’s HSD post-hoc test results show that the dissatisfaction rate of master’s students is significantly higher than that of undergraduates at the 1% level (P < 0.001).

In the ability dimension, undergraduates’ understanding of the most important ability of “Innovation Capability” is higher in mean than master’s and doctoral students, however, the differences did not pass the significance test, indicating that the students in these three grades paid more attention to innovation ability. Master’s students’ dissatisfaction with “User-Centered Thinking” is higher than that of undergraduate students. This difference passed the 5% level test of the analysis of variance (P = 0.019) and the HSD post-hoc test (P = 0.018).

Finally, in the value dimension, there are differences in students in these three education levels regarding the importance of the value of “Ethics and Professional Norms”. This difference has passed the statistically 10% variance test (P = 0.051), and the result of undergraduates shows they attach the highest importance to this value. Regarding the value of “meeting the needs of an inclusive and diverse society,” there was no significant difference in satisfaction levels among students in these three education levels, indicating that the surveyed students were generally dissatisfied with the teaching of this value.

Chi-square test results of the most lacking core competencies at different education levels

Further, the samples are also divided into: undergraduate group, master’s group, and doctoral group. Chi-square test is used to explore whether differences in education levels will affect students’ judgment of their own lack of core competencies. The lack of core competencies among students at different education levels has significant differences in the dimension of ability (P < 0.01). The results in Table 18 demonstrate significant differences in the proportion of students at different education levels reporting a lack of “forward-thinking, strategic insight, and vision for the pharmaceutical industry” (P < 0.01). However, analysis indicated no statistical significance in proportions of students lacking critical knowledge, skills, or values across these educational groups (P > 0.1). Undergraduate students exhibited a more evident deficiency in the ability to think strategically and demonstrate foresight in the pharmaceutical industry, which may be attributed to gaps in curriculum design, teaching methods, or insufficient practical opportunities at the undergraduate level.

Table 18.

Chi-square test results of the most lacking knowledge, skills, abilities and values in different education levels

Indicators	Chi-Square Value	P-Value	Degrees of Freedom	Fisher Exact Test
Knowledge of drug design, formulation, medical translation, and application (most lacking knowledge)	4.15	0.13	2	0.13
Logical reasoning and analysis using mathematics and physics (most lacking skill)	4.27	0.12	2	0.12
Forward-thinking, strategic insight, and vision for the pharmaceutical industry (most lacking ability)	20.75	< 0.001***	2	0.002***
Understanding and addressing inclusive and diverse societal needs (most lacking value)	2.63	0.27	2	0.28

Note: ^*P < 0.10. ^**P < 0.05. ^***P < 0.01; the most deficient index was selected from the index with the highest proportion of students lacking in each dimension

In summary, the results of the differential analysis of the core competencies of students in different education levels show that undergraduates’ awareness of the importance of core competencies is higher than that of master’s and doctoral students, which may be because undergraduates are in the initial stage of professional ability construction and face the pressure of transformation from general education to professional practice. Compared with master’s and doctoral students’ scientific research thinking, undergraduates rely more on practical skills to obtain employment competitiveness. On the other hand, the degree of teaching satisfaction of master students is lower than that of undergraduates and doctoral students, which reveals that the orientation of master education stage is vague. Compared with undergraduates, the repetition rate of master courses is high, but the core competency is difficult to be improved significantly. Compared with doctoral students, master students have lower scientific research thinking. The difference analysis reveals the deficiency of designing differentiated training objectives and training programs for core competency of students in different stages in China pharmaceutical universities.

Differences in core competencies evaluations based on project experience

In addition to the education level, whether students have work experience or project experience may also affect the development of their core competencies. This study used two classification criteria to divide the sample into in-service group and in-school group, as well as project experience group and non-project experience group. The importance, satisfaction rate, and lack of core competencies in each dimension were compared horizontally among students with different experiences. The comparison results are shown in Table 19.

Table 19.

Analysis of differences in knowledge, skills, abilities and values between students with and without work/project experience

	In-service Students (N = 38)	Mean (SD)	In-school Students (N = 881)	Mean (SD)	With project experience (N = 576)	Mean (SD)	With no project experience (N = 343)	Mean (SD)
The most important	Pharmaceutical Chemistry Knowledge	4.50 (0.56)	Pharmaceutical Chemistry Knowledge	4.57 (0.59)	Pharmaceutical Chemistry Knowledge	4.54 (0.61)	Pharmaceutical Chemistry Knowledge	4.57 (0.59)
	Chemical Analysis and Decision-Making	4.39 (0.55)	Drug understanding and evaluation	4.38 (0.72)	Chemical Analysis and Decision-Making	4.43 (0.68)	Drug understanding and evaluation	4.38 (0.68)
	Innovation ability, strong desire for technological innovation	4.39 (0.50)	Innovation ability, strong desire for technological innovation	4.39 (0.74)	Innovation ability, strong desire for technological innovation	4.36 (0.71)	Have forward-looking, strategic thinking and insight into the pharmaceutical industry	4.42 (0.71)
	Ethics, morals, and norms	4.50 (0.51)	Ethics, morals, and norms	4.43 (0.70)	Ethics, morals, and norms	4.43 (0.73)	Ethics, morals, and norms	4.43 (0.67)
The Most Dissatisfied forProfessor	Drug economic management, pharmaceutical management	4.05 (0.61)	Drug economic management, pharmaceutical management	3.71 (1.03)	Artificial Intelligence	3.70 (1.01)	Drug economic management, pharmaceutical management	3.71 (1.04)
	Data collection, refining, processing and other skills (software)	4.00 (0.57)	Project’s Economic Decision Optimization	3.90 (0.93)	Project’s Economic Decision Optimization	3.94 (0.89)	Judgment and risk assessment skills	3.89 (0.91)
	Project’s Economic Decision Optimization	4.00 (0.62)	User-centered Thinking	3.65 (0.89)	User-centered Thinking	3.93 (0.86)	Leadership	3.96 (0.89)
	Meeting the needs of an inclusive and diverse society	4.08 (0.59)	Meeting the needs of an inclusive and diverse society	4.18 (0.79)	Meeting the needs of an inclusive and diverse society	4.17 (0.81)	Meeting the needs of an inclusive and diverse society	4.18 (0.78)
	In-service Students	N(%)	In-school Students	N(%)	With project experience( N  = 576)	N(%)	With no project experience( N  = 343)	N(%)
Most lacking	Drug design, preparation, medical transformation, and application	15 (39.47%)	Drug design, preparation, medical transformation, and application	360 (40.86%)	Artificial Intelligence	234 (40.63%)	Drug design, preparation, medical transformation, and application	157 (45.77%)
	Drug understanding and evaluation	9 (23.68%)	System design and verification	259 (29.40%)	Use mathematics and physics for logical reasoning and analysis	247 (42.88%)	Use mathematics and physics for logical reasoning and analysis	132 (38.48%)
	Have forward-looking, strategic thinking and insight into the pharmaceutical industry	20 (52.63%)	Have forward-looking, strategic thinking and insight into the pharmaceutical industry	324 (36.78%)	Have forward-looking, strategic thinking and insight into the pharmaceutical industry	224 (38.89%)	Have forward-looking, strategic thinking and insight into the pharmaceutical industry	120 (34.98%)
	Meeting the needs of an inclusive and diverse society	19 (50.00%)	Meeting the needs of an inclusive and diverse society	479 (54.37%)	Meeting the needs of an inclusive and diverse society	293 (50.87%)	Meeting the needs of an inclusive and diverse society	205 (59.77%)

Judging from the comparative analysis of whether students have work experience, the difference in core competencies between in-service students and in-school students is mainly reflected in importance evaluation. Working professionals pay more attention to the knowledge of “Drug Design Applications” (mean = 4.05), “Systems Thinking” (mean = 4.39), and “Strategic Foresight” (mean = 4.29), as well as more in-depth core competencies. Students still pay more attention to basic knowledge such as “drug-related chemistry knowledge” (mean = 4.57), “drug understanding and evaluation” (mean = 4.38), which is closely related to the learning or work needs of different types of students. In-service students’ learning goal is to solve the main point of current work and emphasize immediate application, while in-school students’ training goal is to reserve long-term and build professional capital for the future, so there are differences in their views.

Project experience is characterized by context and problem, and is a process of establishing connections between interdisciplinary knowledge and its practical application. It is a deep learning experience for students. From the comparative analysis of students with and without project experience, we found that in terms of importance evaluation, students who have project participation experience place more emphasis on “innovative ability and strong desire for technological innovation” (mean = 4.36); In terms of satisfaction evaluation, students with project experience have the lowest average satisfaction with “artificial intelligence” knowledge, at 3.70. In terms of lack of core competencies, 40.63% of students with project experience believe that they urgently need to supplement their knowledge in “artificial intelligence”, which is significantly different from students who have not participated in the project. It can be seen that students’ innovation projects reconstruct the ability system of pharmaceutical students, and also reveal the shortcomings of traditional knowledge system.

Curriculum development and design of core competency education for pharmaceutical students

Through the analysis of the knowledge, skills, abilities and values of the core competency of pharmaceutical students, we believe that pharmaceutical higher education should focus on building a curriculum framework that is scientific, general, innovative, practical and humanistic when developing the core competency curriculum system for school students or even a wider group of pharmaceutical students, as shown in Table 20.

Table 20.

Example of core competency curriculum development

Design Angle	Core Curriculum		Core Competency Enhancement	Applicable Student Groups
Scientificity	Medicinal Chemistry Gene Therapy …	Drug Design skills Mathematical logic inference …		In-school Students undergraduate Students
Generalizability	Introduction to Pharmacy Principles of Pharmacology …		Fundamentals of pharmacy Drug Comprehension Assessment …	In-school Students undergraduate Students
cross-sectional edge	Artificial Intelligence in Medicine Bioinformatics …		Medical Information Competency Innovative Drug R&D Thinking …	Students with project experience Master Doctoral
Practicality	Pharmaceutical Production Training Clinical Application of Drugs …		Drug Production Process Tool and Equipment Operation …	In-service Students undergraduate Students
Humanistic Care	Pharmaceutical Ethics Community Health Service Practice …		Medical ethics Clinical Humanistic Care …	In-school Students In-service Students

Discussion

China’s pharmaceutical industry is facing a critical transition from imitation-driven to innovation-led development, intensifying the demand for innovative and application-oriented talent. This necessitates comprehensive reforms in both educational frameworks and pharmacy students’ core competency cultivation. Under the background of Global Minimum Essential Requirements in Medical Education (GMER), developed countries such as the United States and the United Kingdom have established a framework for cultivating six core capabilities of ACGME and GMC, which can provide scientific guidance for the cultivation of core competencies of pharmaceutical students [18]. However, the core competencies education of pharmacy students in Chinese universities is in its infancy, and the curriculum training system is out of touch [5]. This study constructs an index system based on competency-based education (CBE) theory and student development theory (SDT) for evaluation of core competencies of pharmaceutical students, and analyzes the importance of core competencies, cognition, teaching satisfaction and core competencies deficiency of current pharmaceutical students in four dimensions: knowledge, skills, ability and values. Our findings deliver actionable insights for pharmaceutical educators and education researchers advancing evidence-based curricular reforms.

Firstly, in the knowledge dimension, pharmaceutical students underestimate the significance of “big data” and “artificial intelligence” competencies (mean scores: 4.08 and 4.00, respectively), while nearly 40% acknowledge deficiencies in these areas. Students have increasingly expressed explicit demands for courses focusing on AI, big data, and new pharmaceutical technologies [19]. Working professionals, in particular, have highlighted the necessity for more robust instruction in data-related skills. In today’s “Internet+” era, curricula must evolve to embrace interdisciplinary integration. This growing focus on strengthening knowledge in pharmaceutical informatics directly aligns with Fox’s emphasis on the urgent need for such courses. Based on the theory of ability education, the goal of college education should attach importance to the training of students’ future job adaptability. However, the lack of artificial intelligence curriculum causes the mismatch between students’ ability and their jobs. A global study shows that the lack of AI knowledge in the classroom is not conducive to the cultivation of innovative thinking and enterprising consciousness, and also affects the improvement of students’ comprehensive competencies level [20]. In the skill dimension, students prioritize cultivating “drug understanding and evaluation” competencies. This is because based on student development theory, undergraduates, have their understanding of drugs mainly based on their chemical structure [21]. Mastering basic knowledge of drugs is the underlying foundation and basic logic for responding to changes in the pharmaceutical industry. However, students’ understanding of the importance of project management skills such as “analysis and judgment, risk assessment” and their professional teaching satisfaction are insufficient, and it hasn’t reached maturity yet. The reasons behind this phenomenon may be multifaceted. Courses in schools are mainly based on knowledge transmission, while risk assessment skills are linked to the practical application of the pharmaceutical industry which are rarely addressed in classrooms [22]. On the other hand, mastering the advanced skill of project management is not easy, students need to have multi-tasking and excellent comprehensive core competencies [23]. To sum up, students’ views on the importance of core competencies and satisfaction with teaching are positively correlated. At present, pharmaceutical students’ understanding of the importance of new knowledge such as artificial intelligence and comprehensive skills such as project management needs to be improved.

Secondly, analysis of students’ self-identified competency gaps reveals two notable findings. First, students’ evaluation of the importance and satisfaction of “Pharmaceutical Chemistry Knowledge” and “Drug understanding and evaluation” competencies (both exceeding 85%), significant deficiencies persist in “Drug design, preparation, medical transformation, and application knowledge” (40.8%). This divergence may be because the existing curriculum system is already well constructed. However, according to student development theory, problems arise in the application of theory to practice [24], and students have particularly weak skills in innovative drug design, clinical transformation and application, which need teachers’ guidance. The reason behind this phenomenon may be that traditional pharmacy education has long been centered on the “chemistry-biology” model, emphasizing the integrity of the subject theoretical system, while practical teaching is only a theoretical supplement [25]. The number of practice bases such as hospitals, pharmacies, pharmaceutical companies, etc. is limited, as a result, students lack such innovative training [26]. Additionally, we found that students lack the ability to “Strategic and Forward-Thinking Insight into the Pharmaceutical Industry” and the values of “Meet the needs of an inclusive and diverse society”. China’s pharmaceutical industry is facing a period of strategic transformation. The innovative development of the industry and the survival of competition require pharmaceutical students to have profound strategic thinking and a value mission of diversified development. However, Chinese Pharmaceutical Universities have paid too much attention to a drug chemical synthesis and preparation, etc., and has neglected macro-curriculums such as pharmacoeconomics, health policy analysis, and global health governance—misaligned with competency-based pharmaceutical education. Therefore, this research suggests reforming evaluation mechanisms to enhance overall values. Student development should be guided by comprehensive evaluation systems, with educational gaps identified through student perspectives while fostering patient-outcome-aligned competencies [27]. Education concepts should be updated in a timely manner and upgraded the education curriculum system. Core competencies required for pharmaceutical talent, according to student perspectives, must incorporate both fundamental knowledge (mathematics, physics, and chemistry) and domain-specific expertise in areas such as pharmaceutics, translational medicine, and drug applications. These results, which vary significantly across different educational levels and project involvement, inform recommendations designed to address student needs, encourage proactive learning approaches, and enhance the development of core competencies among pharmacy students.

At last, cross-cohort competency differentials reveal undergraduates demonstrate heightened awareness of core competency importance compared to graduate students (Master’s/PhD), with statistically significant variance in knowledge (P < 0001) and value dimensions (P = 0.051). Conversely, Master’s students exhibit superior teaching satisfaction relative to undergraduates and doctoral candidates. The reason for this difference is due to fundamental differences in educational goals, evaluation mechanisms and career development paths at different stages [28]. In terms of educational goals, for undergraduates, the courses are the core carrier for building a pharmacy knowledge system. The theoretical knowledge learning of basic subjects such as pharmacy is directly related to graduation credits and degree acquisition, while the focus of master’s and doctoral students turns to scientific research innovation and problem solving. Course learning has taken a secondary position, which is not a direct reflection of core competencies [29]. The evaluation mechanism for colleges and universities to improve core competencies for students in different stages of school is also based on this logic. More importantly, there is a clear differentiation of career goals among different student groups. For example, undergraduates or students who do not have work experience believe that they will engage in standardized work such as drug synthesis and quality inspection in pharmaceutical companies after graduation, course knowledge is their direct skill tool, and it determines job adaptability [30]. When students enter the master’s or doctoral degree study stage, or have scientific research project experience or work experience [31], they believe that applied technology, innovative spirit, and forward-looking thinking have replaced course knowledge and have paid more attention to practical skills. This research finding means that pharmaceutical educators need to respect student group differences when reforming the pharmacy education system. Gender factor was included in the questionnaire data collection. However, the results of variance analysis showed that there was no significant difference among different gender students. This analysis result was different from the survey result of Stith et al. on medical students’ satisfaction with clinical education [32], which needs to be further confirmed by subsequent research.

The analysis of core accomplishment of pharmaceutical students provides beneficial enlightenment for curriculum reform in pharmaceutical universities, which is an inevitable choice to respond to the overall development of core accomplishment of pharmaceutical students. In terms of science, the content of courses needs to keep up with the forefront trends of disciplines, such as gene therapy, artificial intelligence drug design, etc. and strengthen the systematicness of knowledge; in terms of general knowledge, modular courses, such as basic, clinical and social pharmacy modules that promote educational fairness and accessibility. Innovative reforms are not only reflected in the update of course content, but also require the adoption of innovative teaching methods and evaluation systems. Introduce artificial intelligence teaching content, immersive virtual simulation experiment and other courses to improve students ‘innovative thinking ability to solve complex problems. Practicality is the foundation of pharmaceutical education, increase the proportion of practical courses, establish school-enterprise collaborative training base, helping students complete the leap from theory to practice. In the dimension of humanistic care, courses such as drug ethical decision-making and health sociology should be added, incorporating ethical norms, guiding students to carry out pharmaceutical practice based on patients’ needs.

In the curriculum reform of pharmaceutical universities, there is a dislocation of value orientation among teachers, students and enterprises. Teachers focus on the integrity of discipline system, the depth and forefront of theoretical knowledge, pay attention to the cultivation of scientific research accomplishment and academic norms, and relatively lag behind in responding to the ever-changing industrial practice needs. This differs from students’ core concerns for improving employment competitiveness and longing for more practical operations and clear career development path guidance. This requires teachers, students and enterprises to establish a “trinity” curriculum consultation and co-construction mechanism.

Pharmacy higher education needs to establish a scientific benefit distribution and risk sharing mechanism among stakeholders such as schools, industries, and students. The rights, responsibilities and interests of all parties are clarified through contractual management, so as to ensure that pharmacy higher education forms a reciprocal mechanism and sustainable development trend among stakeholders [33]. It is necessary to consider various factors, so as to meet the maximum rights and interests of multiple stakeholders [34], forming a student cultivation model with multi-subject coordination of government, industry, academia and research, and jointly promote the development of students’ core competencies [35].

Conclusions

To address the strategic development needs of the pharmaceutical industry in the new era, core competencies education for pharmacy students has become essential. The cultivation of core competencies in Chinese pharmacy students has long been hindered by issues including lagging educational concepts and insufficient system coordination. Accordingly, this study applied a questionnaire survey method to determine how Chinese pharmaceutical students currently evaluate core competencies education in universities; through this approach, limitations in the professional cultivation of their core competencies were identified. Findings from the study point towards several recommendations: pharmaceutical curriculum reform should be implemented with five dimensions: scientific, general, innovative, practical and humanistic care, strengthen the construction of pharmaceutical-based courses, and increase AI-driven innovation education. Attention should also be paid to cultivating systematic thinking, forward-looking thinking, and multiple abilities in pharmaceutical students. Moreover, the study argues for the significance of workplace education when compared with traditional classroom education, particularly in helping students establish logical thinking to analyze problems and solve practical problems. To better realize the all-round development of pharmacy students, pharmacy educators are encouraged to explore the establishment of a differentiated training model in order to strengthen students’ application ability and ethical norms. Such models would involve designing differentiated training programs that target the weak links of core competencies in pharmacy students at different stages and with varied experiences.

Limitations

This study, through the perspective of pharmacy students, investigates core competencies, elucidates students’ actual understanding and developmental needs regarding these competencies, and examines the implementation of university education. It expands the relevant literature and makes a unique contribution to the field. Additionally, by reviewing literature and conducting expert interviews, this research establishes a systematic pathway for enhancing the core competencies of pharmacy students, based on a widely recognized framework.

However, since the study was conducted at an institution affiliated with a national ministry, where the sample of pharmacy students is relatively comprehensive and pharmaceutical education is well-developed, the findings may not be directly applicable to local universities with varying educational resources. Future research should explore the applicability of these findings across different student demographics and further refine the implementation pathways. Moreover, while the study analyzes questionnaire data quantitatively, core competencies, as a complex capability structure, may not be fully captured by quantitative metrics alone. Although differences in perceptions among groups were addressed in the discussion, the specific reasons warrant further verification through annual surveys and in-depth interviews to supplement the findings and provide insights for the reform of higher pharmaceutical education.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contributions

Juan Chen designed and conducted the survey, drafted and revised the manuscript, and produced the final version. Xiaohang Zhao and Wei Chen were in charge of guiding and refining the data analysis of the survey. Jiayu Li was responsible for the bulk of the manuscript translation. The corresponding author, Cheng Jiang provided coordination for the survey. Xinran Wang contributed insightful recommendations to the study.

Funding

The study was supported by. 1.“Research and Practice of the “Industry Park-Based Education” Model at the College of Excellence in Biomedical Engineering” (project number: JGKT25_C025). 2.“Education and Teaching Reform Project of China Pharmaceutical University”, (project number: 2022JBGS02) 3.“Integration of Industry and Education, Innovation Driven, and the Urgent Need for Pharmaceutical Engineering Technology Talent Training Model Research and Reform in the Industry“(project number. 2023JSJG077). 4.“Exploring Career Competency Enhancement for Industry-Track Teachers in the ‘Industrial Park’ Education Model“(project number. 2025XJYB120).

Data availability

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

Declarations

Ethics approval and consent to participate

Ethical approval for the study was obtained from the ethics committee of China Pharmaceutical University (Approval Date. CPU-2024047). Our research strictly adhered to the Helsinki Declaration, all original studies have been approved by the corresponding ethical review board, and the participants provided their informed consent. In addition, no individual-level data were used in this study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Clinical trial number

Not applicable.