Higher Education Studies, Issue: Vol.16, No.4

The Hierarchical Cultivation Path of AI Literacy for Aviation Equipment Instructors under the SAMR Framework

Tue, 04 Aug 2026 11:39:27 +0000

Artificial intelligence technology is accelerating the transition of military education towards intelligence, and the AI literacy of instructors in aviation equipment training institutions has become an important support for improving the quality and efficiency of maintenance support talent cultivation. This paper, using the SAMR technology integration framework and the "Fundamentals of Electrical Engineering" course as a specific approach, clarifies the main connotations of artificial intelligence literacy of instructors, analyzes the typical predicaments existing in the four levels of substitution, enhancement, modification and remodeling, and thereby proposes a systematic improvement path covering cognitive advancement, ability leap, thinking remodeling and mechanism guarantee. The article argues that the SAMR model provides a usable reference for the stratified cultivation of teachers' AI literacy and has certain practical value for promoting the teaching reform and the improvement of teachers' level in aviation equipment training institutions.

Enhancing Pre-service Teachers’ Scientific Inquiry Questioning through Generative AI-Supported Scaffolding

Thu, 06 Aug 2026 11:30:47 +0000

This study examined pre-service science teachers’ scientific inquiry questioning ability and the types of inquiry questions generated before and after participating in learning activities using an AI-supported scaffolding strategy. A one-group pretest-posttest design was employed. The research instruments consisted of (1) learning activities using an AI-supported scaffolding strategy, (2) a situational assessment of scientific inquiry questioning ability, and (3) criteria for evaluating scientific inquiry questions. The findings revealed that students’ scientific inquiry questioning ability improved from a moderate level before the intervention to a high level after the intervention, with the difference being statistically significant at the .05 level. In addition, the predominant type of students’ questions shifted from reasoning questions before the intervention to predictive or forecasting questions after the intervention. Students also reported that AI-generated feedback, together with instructor guidance, helped them identify weaknesses and refine their scientific inquiry questions. These findings suggest that AI-supported scaffolding can serve as a practical approach for supporting pre-service science teachers and science educators in designing learning activities that promote scientific inquiry in 21st-century classrooms.

Factors Influencing Vocational Students' Acceptance of Generative AI for Learning: A PLS-SEM Approach

Sat, 08 Aug 2026 11:42:38 +0000

The present study aimed to: (1) examine the levels of perception and opinion of vocational students toward factors influencing their acceptance and use of Generative AI (GenAI) for learning; (2) develop and validate a structural model of causal relationships among such factors; and (3) analyze the direct, indirect, and total effects of predictor variables on behavioral intention and actual use behavior. A sample of 500 students enrolled in Vocational Certificate (VC) and Higher Vocational Certificate (HVC) programs under the Office of the Vocational Education Commission was selected through stratified random sampling. Data was collected using a seven-point Likert scale questionnaire (reliability = 0.978) and analyzed via descriptive statistics and Partial Least Squares Structural Equation Modeling (PLS-SEM) using ADANCO software.

Results revealed that vocational students held highly positive opinions regarding GenAI acceptance across all dimensions. The PLS-SEM analysis confirmed satisfactory model fit. Performance expectancy (β = 0.149, p < 0.05), effort expectancy (β = 0.138, p < 0.05), social influence (β = 0.127, p < 0.05), hedonic motivation (β = 0.194, p < 0.01), personal innovativeness (β = 0.262, p < 0.01), and trust (β = 0.147, p < 0.01) all had significant positive effects on behavioral intention. Privacy did not exert a significant effect on behavioral intention. Behavioral intention strongly predicted actual use behavior (β = 0.625, p < 0.01), with the model explaining 79.97% of variance in behavioral intention and 39.05% in use behavior. Findings highlight the growing importance of GenAI in vocational education and suggest that institutions should promote AI literacy, ethical AI practices, and supportive learning environments.

Transformational Leadership, Work Environment and Internal Marketing Enhance Organizational Effectiveness

Mon, 10 Aug 2026 10:36:57 +0000

This paper uses Chinese higher education institutions as the research context, constructs a theoretical model based on survey data from 438 employees, and conducts empirical testing to explore the mechanisms by which transformational leadership, work environment, and internal marketing affect organizational effectiveness. Current research rarely explains the relationship among transformational leadership, the work environment, and organizational effectiveness from the perspective of internal marketing mechanisms. This study reveals the mediating path of internal marketing in higher education governance. The study uses descriptive statistical analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modelling (SEM) to test the theoretical model. The results show that both transformational leadership and the work environment have significant positive effects on internal marketing and organizational effectiveness; internal marketing also has a significant positive effect on organizational effectiveness. Furthermore, internal marketing plays a mediating role between transformational leadership and organizational effectiveness, as well as between the work environment and organizational effectiveness. This study expands the theory of internal marketing in the context of non-profit organizations. It provides theoretical support and management guidance for improving the governance effectiveness of higher education institutions.

Latent Profiles of AI Literacy, Self-Directed Learning, and Creative Self-Efficacy among Art Students and Their Associations with Lifelong Learning Competence

Fri, 21 Aug 2026 03:49:48 +0000

Generative artificial intelligence (AI) is reshaping the resources art students use for learning and creative production, but technological knowledge, learning regulation, and creative confidence may not develop in parallel. This cross-sectional study used latent profile analysis to examine how self-reported AI literacy (AIL), self-directed learning (SDL), and a brief four-item contextualized measure of creative self-efficacy (CSE) co-occurred among 502 art students from three universities in Shaanxi Province, China. Four profiles were retained as a descriptive representation of the sample: moderate AIL-lower SDL/CSE (15.7%), lower AIL-moderate SDL/CSE (18.7%), higher AIL-moderate SDL/CSE (32.5%), and higher AIL-higher SDL/CSE (33.1%). CSE item loadings ranged from .673 to .724, with alpha = .785, omega = .786, and average variance extracted = .479, indicating adequate internal consistency but limited content coverage and marginal convergent validity. Replacing the four CSE items with their composite mean produced high classification agreement with the primary model (adjusted Rand index [ARI] = .869); removing CSE reduced agreement (ARI = .729) but retained substantial heterogeneity. Neither sensitivity specification uniquely supported four rather than three profiles. Prior AI-course experience distinguished the first profile from the higher AIL-higher SDL/CSE profile, and self-reported lifelong learning competence increased across the four profiles. The findings support flexible course designs, but the profiles remain sample- and specification-bound and should not be used for individual screening.

The Development of Digital Innovative Learning Media Based on the Professional Learning Community (PLC) Process for Participatory Learning

Fri, 21 Aug 2026 10:28:28 +0000

This mixed-methods research and development study developed and preliminarily evaluated an integrated system of digital innovative learning media for participatory learning through a professional learning community (PLC) process. The reported study followed four R&D phases and focused on completed development evidence rather than the unfinished student-outcome component of the larger project. Participants included 500 teachers in a province-wide needs survey, 92 stakeholders in the selected target area, nine experts, 20 teachers and 120 students in a try-out, and 200 teachers in a one-group pretest-posttest professional-development study. Data were analyzed using means, standard deviations, the modified priority needs index (PNImodified), E1/E2 efficiency, a paired-samples t test, the standardized mean change d_av, and content analysis. Six design components were validated at high to highest levels. Khon Kaen Primary Educational Service Area Office 2 had the highest development need (PNImodified = 0.58) and was selected as the implementation site. The KruDigital cloud platform comprised four modules and 15 screens, supported 20 augmented-reality and gamified reading-literacy media sets, and integrated a three-day workshop with eight weeks of school-based PLC, lesson study, and coaching. Try-out efficiency was 92.35/88.87, exceeding the predetermined 80/80 development criterion. Teachers' knowledge scores increased from M = 16.84 (SD = 3.92) to M = 25.67 (SD = 2.88), t(199) = 34.52, p < .001, d_av = 2.57. These findings provide developmental and preliminary evidence of feasibility and teacher learning; they do not establish causal effects or student learning outcomes.

Enhancing Knowledge, Attitudes and Practical Skills of the International Standards System for the Environmental Management (ISO14001: 2015)

Sat, 22 Aug 2026 12:05:12 +0000

The purposes of this research were to develop curriculum of the international standards system for the environmental management (ISO 14001: 2015) to be efficiency and effectiveness, to study and compare knowledge, attitude and practical skills about the international standards system for the environmental management on pre-test and post-test of the training and to compare knowledge, attitude and practical skills of the sample with different genders and ages. The sample were 34 community enterprise group representatives in Yang Talat district, Kalasin province, who voluntarily participated in the training. The tools were curriculum of ISO 14001: 2015, knowledge test, attitude test and practical skills test. The data were analyzed by frequency, percentage, mean, standard deviation and hypothesis testing using t-test and F-test (One-Way MANOVA, One-Way MANCOVA). The finding showed that: 1) The curriculum of ISO 14001: 2015 was efficiency of 89.25/84.46, effectiveness of the activity index was equal to 0.7809. The sample’s average score of knowledge of ISO 14001: 2015 was more and effected to increased sample progress after learning at 78.09 percent. 2) The sample’ average scores of knowledge, attitude and practical skills about ISO 14001: 2015 on post-test were statistically significance higher than on pre-test (p<.05). 3) There was no difference of average scores of knowledge, practical skills about ISO 14001: 2015 of the sample with different genders. There was difference of average scores of attitudes toward ISO 14001: 2015 of the sample with different genders statistically significance (p<.05). There was no difference of average score of knowledge, attitude and practical skills about ISO 14001: 2015 of the sample with different ages.

Comfort versus Legitimacy? Student Perspectives on In-Course, Online, and AI-Mediated Assessment

Wed, 26 Aug 2026 11:26:06 +0000

This study examines how final-year undergraduate economics students evaluate contemporary assessment practices in a period of rapid digital change. Using survey data from a cohort of final-year undergraduate economics students at a UK university, it analyses perceptions of in-course assessment, online assessment, and generative AI in relation to fairness, inclusivity, learning support, stress, and procedural legitimacy. Rather than treating assessment attitudes as one-dimensional, the paper combines item-level evidence with a small number of transparent summary measures to distinguish between different sources of student support and concern.

The findings reveal four main patterns. First, students evaluate in-course assessment positively overall, with especially strong support for its fairness and inclusivity. Second, this support is not unconditional: students value the reduction of final-exam stress through diversified assessment more strongly than they endorse the proportionality of in-course workload. Third, students view online assessment more positively in terms of comfort and convenience than in terms of fairness, integrity, and broader legitimacy. Fourth, generative AI is associated with substantial anxiety about penalties and uncertainty over acceptable use.

Although exploratory, the results highlight three practical priorities for assessment design: preserving the fairness and inclusivity benefits of diversified assessment, improving workload calibration, and developing clearer governance around AI use. More broadly, the study shows the value of treating student views on assessment as multidimensional, especially in increasingly digital and AI-mediated educational environments.

A Program to Strengthen Servant Leadership of University Library Department Heads in Nanning

Fri, 28 Aug 2026 02:25:19 +0000

The objectives of this research were: (1) to explore the existing situation, desirable situation, and the needs to develop servant leadership of university library department heads in Nanning; (2) to develop a program to strengthen servant leadership of university library department heads in Nanning. The study employed a mixed-methods research design consisting of two phases. Phase 1 explored existing situations, desirable situations, and the needs to develop servant leadership. The sample consisted of 202 library leaders, department heads, frontline librarians from five universities in Nanning. The research instrument was a 5-rating scales questionnaire. Phase 2 developed a program to strengthen servant leadership of university library department heads. Five experts in servant leadership were interviewed, and seven experts evaluated the program. Statistics used to analyze data were mean, standard deviation, and modified priority needs index.

The research found that: (1) The elements of servant leadership of university library department heads comprised four components: altruism, vision, empowerment, and influence, all of which were evaluated at a very high level of appropriateness. (2) The existing situation in all and each individual component was at a moderate level. The desirable situation in all and each individual component was at a very high level. The priority needs were ranked from highest to lowest as follows: Influence, Empowerment, Altruism, and Vision. (3) The program consisted of five major components: Rationale, Objectives, Content, Development Methods and Activities, and Measurement and Evaluation. The overall evaluations of the program’s appropriateness, feasibility, and utility were at a very high level.

Understanding Technology Acceptance in Virtual Electrical and Electronics Laboratories: Evidence from Chinese Higher Vocational Students

Mon, 31 Aug 2026 03:18:48 +0000

Vocational education systems worldwide invest substantial capital in virtual simulation infrastructure, yet virtual laboratories deliver instructional value only if students continue to use them. This study applied the Technology Acceptance Model (TAM) to explain acceptance of virtual electrical and electronics laboratories, a context distinguished by imperceptible target phenomena, physical hazard, and a strong emphasis on fault diagnosis, and a population largely absent from the international acceptance literature. Cross-sectional survey data were collected from 409 students. The participants were higher vocational students enrolled at Sichuan Vocational and Technical College of Communications, China. All respondents had prior experience using virtual electrical and electronics laboratories as part of regular coursework, and the data were analyzed using partial least squares structural equation modeling (SmartPLS 4; 5,000 bootstrap subsamples), pairing conventional explanatory assessment with out-of-sample predictive evaluation via PLSpredict. All four hypotheses were supported. Perceived ease of use predicted perceived usefulness (β = 0.491) and attitude toward use (β = 0.252); perceived usefulness predicted attitude (β = 0.497); and attitude predicted behavioral intention (β = 0.597). The model explained 24.1%, 43.4%, and 35.6% of the variance in usefulness, attitude, and intention respectively, and returned positive Q²predict values for every endogenous indicator. Two findings refine TAM in this setting. Perceived usefulness exerted about twice the direct influence on attitude as ease of use (f² = 0.332 versus 0.085), with about half of ease of use's total effect transmitted indirectly through usefulness, indicating that usability operates as an enabling rather than a driving belief. Attitude, in turn, served as the complete conduit linking both beliefs to intention. For experienced vocational learners, instrumental value rather than operational convenience governs continued use, implying that design and procurement should prioritize curricular alignment and diagnostic depth over interface sophistication.

Predicting Teachers' Behavioral Intention to Adopt Generative AI in Teaching: An Integrated TAM-UTAUT Regression Model

Tue, 01 Sep 2026 02:25:22 +0000

Generative artificial intelligence (GenAI) has entered classrooms faster than most institutions have been able to formulate policy, yet its instructional value ultimately depends on whether teachers choose to use it. This study examined the determinants of teachers' behavioral intention (BI) to use GenAI in teaching, drawing on an integrated Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT) framework. Five predictors were specified: perceived ease of use (PEoU), perceived usefulness (PU), social influence (SI), facilitating conditions (FC), and anxiety (ANX). A cross-sectional survey was administered to 500 in-service teachers drawn from three Chinese educational institutions spanning medical higher education, vocational higher education, and primary education. Each construct was operationalized as a composite mean of its constituent items, and the model was estimated using the Regression module of SmartPLS 4 with bootstrapping (5,000 subsamples) to obtain confidence intervals. Collinearity diagnostics were acceptable (VIF = 1.046-1.238). The model accounted for 32.7% of the variance in behavioral intention (adjusted R² = .320). Perceived usefulness was the strongest predictor (β = .228, p < .001), followed by facilitating conditions (β = .206, p < .001), perceived ease of use (β = .198, p < .001), and social influence (β = .195, p < .001). Contrary to expectations, anxiety exerted no significant effect (β = .018, p = .631), with a bootstrap confidence interval that spanned zero. The findings indicate that teachers' adoption decisions are jointly driven by instrumental value and institutional provisioning, and that generalized technology anxiety is not, in itself, a barrier among teachers who already have practical exposure to GenAI. Implications for professional development design and institutional AI policy are discussed.

Industrial Engineering Students’ Acceptance of PLC Learning: A PLS-SEM Analysis Based on the Technology Acceptance Model

Wed, 02 Sep 2026 13:26:42 +0000

The increasing adoption of Industry 4.0 technologies has intensified the need for industrial engineering graduates to acquire competency in Programmable Logic Controller (PLC) programming and industrial automation. Despite the growing implementation of PLC simulation software and digital laboratories, limited empirical research has examined the factors influencing students' acceptance of PLC learning. This study applied the Technology Acceptance Model (TAM) to investigate the relationships among perceived ease of use (PEOU), perceived usefulness (PU), attitude toward PLC learning (ATT), and behavioral intention to use PLC learning systems (BI). A quantitative cross-sectional survey was conducted with 399 undergraduate students from Sichuan Vocational and Technical College of Communications in China who had experience in PLC-related courses. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4. The measurement model demonstrated satisfactory reliability and validity, with outer loadings ranging from 0.797 to 0.886, composite reliability values between 0.882 and 0.911, and average variance extracted (AVE) values between 0.651 and 0.773. Both the Fornell-Larcker criterion and the heterotrait-monotrait ratio confirmed adequate discriminant validity. The structural model supported all proposed hypotheses. Perceived ease of use significantly influenced perceived usefulness (β = 0.416, p < .001) and attitude (β = 0.196, p < .001), perceived usefulness positively affected attitude (β = 0.372, p < .001), and attitude exerted the strongest influence on behavioral intention (β = 0.511, p < .001). The model explained 17.3% of the variance in perceived usefulness, 23.8% in attitude, and 26.1% in behavioral intention. The findings indicate that students' acceptance of PLC learning is most strongly associated with the perceived educational value of PLC instruction, while positive attitudes serve as the most important predictor of continued intention to engage with PLC learning. Multi-group analysis, preceded by measurement invariance testing, indicated that the effect of perceived ease of use on perceived usefulness was significantly stronger for female than for male students, while the model was otherwise invariant across gender, year of study, and prior PLC experience. These results provide practical implications for designing learner-centered PLC curricula that integrate user-friendly learning environments with authentic industrial automation experiences.

Who Offloads and Who Co-Creates? Comparing Undergraduate and MBA Learners in Agent-Driven Business English Project-Based Learning

Wed, 02 Sep 2026 13:34:54 +0000

Agent-driven instructional models are spreading rapidly in language education, yet the question of for whom such models work—and for whom they carry risks—has received little attention. Using the cognitive offloading-human-AI co-creation continuum as an analytic lens, this study compared two contrasting learner populations under the same agent-driven Business English project-based learning (PBL) model: first-year undergraduates (n = 30) and MBA students (n = 30). The two cohorts were taught by the same instructor with the same textbook and identical agent roles and interaction rules, and completed parallel versions of the same end-of-semester questionnaire (with minor wording adaptations for undergraduates), supplemented by open-ended responses. Analyses combined between-group comparisons, a seven-dimension profile comparison, an exploratory typological cluster analysis of offloading and co-creation, and hierarchical regression. Results showed that the two populations were strikingly similar in offloading containment and across all outcome dimensions: no between-group difference survived Holm correction (|d| <= 0.52), and the only medium-sized item-level difference was confidence in detecting errors in agent output (higher among MBA students, d = 0.67). The typological analysis indicated that the sample divided into a “deeply engaged” type (56.7%) and a “prudent self-reliant” type (43.3%) that cut across both cohorts, with high co-creation and elevated dependence signals co-occurring and the type distribution independent of cohort (p = .193). After controlling for gender, prior generative-AI experience, and use frequency, the incremental explanatory power of cohort approached zero (dR-squared <= .021). The findings suggest that under one and the same rule-governed design, “level is not destiny”: learner level should remain an explicit consideration in the design and scaling of agent-based pedagogy, but the unit of differentiation should descend to learner types, and differentiated design guidelines are derived accordingly.