This study aims to explore and analyze the profile of UPGRIS character values within the context of campus culture development. A mixed-method approach, integrating both qualitative and quantitative methodologies, was employed. The quantitative analysis focused on identifying which UPGRIS character values—Unggul (excellence), Peduli (caring), Gigih (persistence), Religius (religion), Integritas (integrity), Sinergis (synergy)—are most prominent among students, utilizing percentage analysis. The qualitative approach involved a more in-depth examination through Focus Group Discussions (FGDs) to elucidate the meaning and manifestation of these values. A purposive sampling technique was used to select 2,554 students from seven faculties. Data were collected through psychological scales and FGDs. The findings indicate that the most pronounced character value, based on quantitative data, is religion, while excellence ranks the lowest. Notably, persistence is the highest-rated value in first-year students, whereas character traits such as excellence, caring, and integrity peak in the fifth semester. Conversely, it was observed that nearly all character values, including excellence, caring, persistence, religion and integrity, show a significant decline by the seventh semester. These results provide crucial insights into the fluctuations in character development across different stages of academic progression, offering implications for future educational and institutional interventions.
This study investigates the intricate relationships among workplace deviance, employee engagement, and research quality within the context of higher education institutions (HEIs) in Nigeria, specifically in Sokoto State. Grounded in dynamic capability theory, the normative perspective, and employee engagement theory, this study posits that workplace deviance detrimentally influences employee engagement, which in turn adversely impacts research quality. A moderated-mediation model was proposed, suggesting that employee engagement mediates the relationship between workplace deviance and research quality, while also being moderated by institutional support mechanisms. The analysis, conducted using SmartPLS 4, includes an examination of response rates, preliminary data assessment, validation of measurement instruments, and hypothesis testing. The findings reveal a complex dynamic where workplace deviance, when moderated by a supportive institutional environment, indirectly enhances research quality through increased employee engagement. This paradoxical outcome underscores the significance of fostering a positive work culture that can mitigate the adverse effects of deviant behavior, thereby promoting research excellence. The study's theoretical and practical implications suggest that mitigating workplace deviance, enhancing employee engagement, and encouraging participatory decision-making are crucial for improving research outcomes. Future research is encouraged to further explore the interplay between workplace deviance and employee engagement and to assess the generalizability of these findings across diverse institutional contexts.
A comprehensive Water Conservation Awareness Scale was developed to assess the awareness levels of preschool children regarding water conservation. This scale encompasses four distinct dimensions: personal action awareness, daily activity awareness, outdoor water use awareness, and shared responsibility awareness. The study involved 471 children from four kindergartens located in Uşak Province. The four-factor structure of the scale was validated through both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), confirming its reliability and construct validity. The overall scale demonstrated a Cronbach’s alpha coefficient of 0.79, indicating a high level of internal consistency. The developed scale is intended to serve as a critical tool for evaluating the effectiveness of educational programs aimed at fostering water conservation awareness among young children. Additionally, it provides valuable insights for the design and implementation of early childhood education initiatives focused on environmental sustainability. The findings are expected to contribute significantly to the promotion of water-saving behaviors from an early age.
In an increasingly competitive market landscape, companies must innovate by allocating a significant portion of product sales revenue, specifically at least 22%, towards research and development (R&D). Collaboration between companies and universities, which actively engage in R&D, is crucial in this context. At Andalas University, the Research and Community Service Institute (LPPM) oversees R&D initiatives and community services, including the management of the Science Techno Park. To achieve commercialization objectives, it is imperative to identify and address the factors that inhibit the commercialization of research products at Andalas University. The Fuzzy Analytical Hierarchy Process (FAHP) method has been employed to ascertain the primary factors impeding commercialization. The research findings indicate that the foremost factor inhibiting commercialization is resource availability, assigned a weight of 0.221. This is followed by intellectual property considerations, with a weight of 0.215, and marketing challenges, with a weight of 0.160. These insights provide a foundational basis for the development of strategies aimed at enhancing the commercialization of research products at Andalas University.
The rapid advancement of the internet industry and the emergence of intelligent production models necessitate a transformative approach to talent cultivation in global universities. The Outcomes-Based Education (OBE) model demonstrates distinct advantages and adaptability within this evolving landscape. By defining explicit learning outcomes, incorporating flexible curriculum designs, emphasizing practical skills, adopting a philosophy of continuous improvement, implementing multi-dimensional evaluation mechanisms, and employing student-centered teaching methods, OBE establishes a robust theoretical framework and practical methodology for developing high-quality artificial intelligence (AI) talents suited to the demands of the new era. This study, centered on graduate students at the Capital University of Economics and Business, proposes three strategic dimensions for curriculum reform grounded in the OBE concept: the objectives of curriculum reform, innovative teaching models, and the implementation of the curriculum. The investigation highlights the significance of value cultivation in discipline construction, the establishment of a diversified talent training system, and the optimization of a scientifically integrated teaching framework. This research offers valuable insights, ranging from policy recommendations to practical applications, aimed at advancing the high-quality development of computer science disciplines in a contemporary context.
The purpose of this article is to explore the multifaceted approach required to address the alarming dropout rates and early leavers from education and training in Romanian pre-university education. We emphasize the necessity of collaborative efforts among families, educational institutions, and policymakers to implement effective strategies. As the method used, the bibliographic research was carried out, developed in parallel with the research on the realities in the field in order to provide data for their processing, accumulating data by interviewing stakeholders, analysis and interpretation. By surveying 557 internal stakeholders, primarily teachers, the research identifies critical elements in successful dropout prevention strategies, such as consistent evaluation, clear organizational environments, and strategic communication. The findings reveal significant gaps, particularly in the analysis of external factors and the recruitment and training of stakeholders, suggesting areas for improvement. Implications: Enhancing dropout prevention efforts requires a holistic approach, incorporating thorough environmental analyses, a shared mission and vision among stakeholders, and improved communication and training initiatives. We conclude that a comprehensive and adaptable strategy, inclusive of all educational stakeholders, is crucial for reducing dropout rates and fostering a supportive educational environment.
In the digital age, technological advancements have reshaped the global educational landscape, prompting governments and educational institutions to recognize the critical role of research and innovative talent in driving societal progress and economic growth. Undergraduate education, as a pivotal phase for cultivating future innovators, faces unprecedented opportunities for transformation. The rise of online teaching models has catalyzed a profound pedagogical revolution, offering both flexibility in learning and significant potential for educational innovation. This study investigates the current state and influencing factors of research quality among undergraduates at the Capital University of Economics and Business within the online teaching model. The analysis is structured around four key dimensions: research preparation, research motivation, research communication, and research organization and management. Targeted recommendations are proposed to enhance these aspects, providing valuable insights for the reform of undergraduate education in the context of online learning. The findings underscore the potential of educational transformation as a development opportunity, advocating for the integration of innovative educational models with technological advancements to better align with the talent cultivation needs of the contemporary era.
The widespread adoption of Learning Management Systems (LMSs) in educational contexts, underscored by their critical role in facilitating cloud-based training across diverse settings, serves as the foundation of this investigation. In the era of increasing integration of technology within higher education, a notable reduction in the costs associated with the creation of online content has been observed. The shift towards remote learning, precipitated by the COVID-19 pandemic, has highlighted the indispensable nature of LMSs in the delivery of specialized content, the application of varied pedagogical strategies, and the promotion of student engagement. Adaptability, defined as the ability to adjust behavior, cognition, and emotional responses in the face of new circumstances, has been recognized as a key factor in the success of online learning. This study employs sophisticated Machine Learning Techniques (MLTs) to explore the determinants of student adaptability, introducing the novel framework of Online Learner Adaptability Assessment using MLTs (OLAMLTs). Through the analysis of comprehensive datasets, which include indicators of student behavior, performance, and engagement within online platforms, MLTs facilitate the identification of patterns and correlations pertinent to adaptability. The OLAMLTs framework applies a retrospective analysis to variables such as technological proficiency, motivation, and self-regulatory capabilities, enabling the provision of customized recommendations for educators. By facilitating targeted educational interventions, the study seeks to address the disparity between the need for adaptable learners and the availability of tools designed to foster this critical attribute. The ultimate aim is to augment the resilience and efficacy of online learning platforms in anticipation of future disruptions, including pandemics or other unforeseen challenges. This research contributes to the ongoing efforts to develop a more adaptive and resilient online learning landscape, marking a significant advancement in the fields of educational technology and pedagogy.
Course evaluation, a critical component for the implementation of outcome-based education (OBE), provides substantial data support. The reliability, validity, and discriminative power of evaluation results are significantly influenced by the choice of course evaluation methods. An effective course evaluation method identifies weak links in the teaching process, offering a foundation and reference for continuous course improvement. This study introduces a course evaluation method based on achievement pathways, establishing the supportive relationship among course-related graduation requirement indicators, course objectives, and achievement pathways. Grounded on formative assessment, a system to quantify the achievement of teaching objectives in courses is constructed. The method has been applied to courses, such as Data Visualization and Software Engineering, at the Beijing Institute of Petrochemical Technology. Practice demonstrates that this method is capable of identifying weaknesses in the course implementation process, providing theoretical foundation and reliable assurance for ongoing course improvement.
In today’s digital age, new technological tools are increasingly becoming an indispensable part of the educational process, particularly in educating children. The development of technology, including tablet computers, and mobile phones, offers numerous opportunities for enhancing teaching methods and fostering children’s development. These technologies offer access to a wide array of digital resources, interactive content, and personalized educational experiences, thereby opening up new methods in education. However, despite the benefits, many studies underscore the potential negative impacts of utilizing new technologies in children’s education. For the above reasons, a study was conducted to examine how new technologies influence children’s learning of geometric shapes. Forty children, evenly distributed by gender and place of residence, participated in the study, undergoing testing using both mobile phones and Tablet PCs. The results revealed statistically significant differences based on the respondents’ gender, place of residence, and the devices through which the tasks were presented, particularly for certain geometric shapes.
Purpose: To provide reference promoting the construction of nursing courses through the analysis of research hot spots on ideological and political education in nursing courses in China; Methodology: CiteSpace and VOSviewer software were used to visualize the pertinent literature that was downloaded from CNKI, Wanfang, VIP database before December 31, 2023; Results: A total of 918 literatures were included, and the publications, authors, institutions, journals, course type, keywords of the literature were analyzed. The number of published papers had increased year by year. Publishing institutions were primarily schools, authors were mostly independent researchers, published journals were relatively concentrated, with most of them being general or provincial journals, and courses are mostly theoretical. Hotspots for current research include the integration of nursing courses in higher vocational colleges and the mining of Ideological and political elements; Conclusions: Curriculum ideology and politics have received extensive attention from nursing educators. In the future, it is necessary to strengthen the exchanges between different research institutions such as schools and hospitals, pay attention to the depth of research, develop educators' political and ideological ability, actively use a variety of teaching methods, and integrate political and ideological elements into the teaching of a diversified curriculum, so as to provide talent guarantee for the realization of "Healthy China".
This investigation examines the influence of ChatGPT on mathematics achievement, with a specific focus on the moderating role of students’ interest in mathematics. A sample of 250 students, encompassing undergraduates pursuing a Bachelor of Science and postgraduates engaged in Masters of Philosophy and Doctor of Philosophy programs in Mathematics Education at Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development (AAMUSTED), Kumasi-Ghana, was selected through random sampling. Employing a quantitative methodology, data were collected via structured questionnaires and analyzed using Amos software, version 23, to test the hypothesized relationships. The findings revealed that student interest in mathematics significantly and positively correlates with the use of ChatGPT, as evidenced by a p-value of less than 1%. Conversely, ChatGPT’s direct influence on mathematics achievement was found to be negative, though not statistically significant, with a p-value of less than 1%. Furthermore, a direct, positive, and statistically significant relationship between students’ interest in mathematics and their achievement in the subject was observed, with a p-value of less than 1%. Notably, the study identified a statistically significant positive moderation effect of students’ interest on the association between ChatGPT usage and mathematics achievement, underlined by a p-value of less than 1%. The findings advocate for a cautious integration of ChatGPT in mathematics education, emphasizing that reliance on artificial intelligence should complement, not replace, traditional learning modalities. Additionally, it is suggested that future research might benefit from employing surveys or self-evaluation tools beyond questionnaires to gather data. This study contributes to the existing body of knowledge by highlighting the nuanced role of student interest in leveraging technology-enhanced learning tools for academic success in mathematics.
Teachers face challenges when conducting their jobs (stress, work overload, lack of resources, lack of time, etc.), which may lead them to psychological problems. With the current information overload and sparsity of resources, it can be challenging to find relevant educational resources promptly. Recommender systems are designed to address the issue of information overload by filtering relevant information from a large volume of data based on user preferences, interests, or observed behavior. A recommender system can help mitigate teachers’ struggles by recommending personalized resources based on teachers’ needs. This paper presents previous works related to recommender systems in education. It highlights their techniques and limitations. Some papers relied on machine learning and/or ontology for building recommender systems, while others relied on a hybrid system comprising several techniques. The most employed recommendation techniques include collaborative filtering (CF), content-based (CB), and knowledge-based (KB) approaches. Each approach has its advantages and limitations. To overcome these limitations, several advanced recommendation methods have been proposed, such as social network-based recommender systems, fuzzy recommender systems, context awareness-based recommender systems, and group recommender systems. Our analysis reveals that existing recommender systems are learner-centered, often lacking an understanding of the teacher’s context. The continuous advancement of recommendation approaches and techniques has led to the implementation of numerous recommender systems and the development of numerous real-world applications. A context-aware personalized recommender system for teachers should consider personal and professional development goals and psychosocial state when presenting a recommendation. Years of experience, access to equipment, and commute time are some of the aspects that should be considered when designing such a system. Moreover, the studies surveyed provided detailed information about their evaluation methodologies. However, the evaluation of these systems is typically conducted using simulated or nonreal students, along with various assessment approaches such as algorithmic performance tests, statistical analysis, questionnaires, and qualitative observations.
Starting from social identity theory, this article explores the importance of interpersonal relationships to the work performance of teachers in private colleges and universities born in the 1990s, and examines the relationship among interpersonal relationship, organizational commitment and work performance. After conducting a questionnaire survey and analysis of 951 teachers from 19 private Colleges and Universities, the results show that aspects of interpersonal relationships, specifically caring for others and self-image, exert a significant positive impact on organizational commitment and work performance; and these factors can enhance the work performance of post-1990s teachers in these institutions through the partial mediating role of organizational commitment. Research shows that the interpersonal relationships established and maintained from public goals or private goals can promote the organizational commitment and work performance of post-1990s teachers in private colleges and universities. Higher level of interpersonal relationship can improve teachers’ identification and sense of belonging to the organization, and then improve their work performance.
The efficacy of political education is pivotal in developing critical thinkers and informed citizens. Traditional methods, however, face challenges such as low engagement, accessibility issues, slow adaptation to changes, and underutilization of technological advancements. This research investigates the transformative impact of integrating Artificial Intelligence (AI) and cutting-edge design strategies into political education courses at Pakistani universities. The study adopts a methodological approach that synergizes AI-based network media with traditional educational practices, subsequently evaluating the implementation’s outcomes through empirical data. The integration of AI into the educational framework has shown remarkable results: a 57% increase in the rate of education post-implementation, a 71% satisfaction rate among students regarding their learning experience, and a political accomplishment (PA) score of 81±4. These metrics indicate a substantial enhancement in the quality of political education. The research underscores the potency of AI-supported communication coaching in elevating political education standards, thereby nurturing political and ideological competencies among students. This modernization, characterized by dynamic, interactive, and globally accessible learning experiences, promises to redefine political education. It effectively dismantles historical barriers, equipping individuals to navigate the complexities of the contemporary geopolitical landscape.
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