College Guidance Research Articles

A Study of Informatization and Data-Driven Career Planning in Career Guidance in Colleges and Universities

Abstract Traditional career planning education and employment guidance is based on lectures and text reading, with a large amount of subjective coloring, which can’t achieve one person one strategy. This paper constructs a college career guidance information recommendation system based on collaborative filtering and K-means clustering to recommend suitable career information with a high potential success rate for students from both subjective and objective aspects. The weights of students’ features are objectively calculated, and the K-means algorithm is improved with the minimum spanning tree method to spontaneously calculate the initial number of categories and the class center value from the data, avoiding the problem of random generation and enhancing the effect of clustering. The system is tested against other models in the dataset to examine its clustering performance. It is found that on the optimal K-mean-square error, the errors of the model in this paper are all less than 0.96, which is the lowest among the algorithms on all terms, and its clustering performance is again verified. The best results on the dataset are achieved by the proposed algorithm, with an HR@20 of 59.31%, which is almost twice the SVD recommendation method. The experiment confirmed the significance of each module in the recommender system. Compared with the recommendation of graduates’ jobs, the system is easier to recommend industries for graduates, and the HR indicator is greater than 80% at the recommendation list lengths of 3 and 5, while the HR@5 of SVD, BPR is below 50%. This study provides useful insights into the integration of cutting-edge information technology career guidance and data mining to aid in career planning.

Exploration on Innovative Models of Ideological and Political Education and Employment Guidance in Higher Vocational Colleges in the New Era Context

Exploration on Innovative Models of Ideological and Political Education and Employment Guidance in Higher Vocational Colleges in the New Era Context

Requirements as for work on board a ship from the perspective of maritime field students and seafarers

Purpose: The study aims to identify the opportunities for improving the employment offers by identifying differences in the requirements as for work on a ship formulated by maritime university students and seafarers. Design/methodology/approach: To achieve the goal, the Kano method was applied, to determine the relationship between the level of requirements fulfilled to work on a ship and the students' and seafarers' level of satisfaction. Findings: It was found that there are differences in how students and seafarers perceive the same requirements for working on a ship. As the perception of these requirements depends on the seafaring experience, shipowners should differentiate the terms and conditions of employment formulated in job offers to the targeted group of potential employees. Research limitations/implications: The survey was conducted among students of only one Polish maritime university and, moreover, only seafarers of Polish nationality participated. Hence, future research in this area may include the identification of the requirements for work on board set by students and seafarers of other countries, as well as the identification of differences in the requirements for future work at sea set by students at the beginning and at the end of their education. Practical implications: The study results obtained may prove helpful to shipowners in adjusting the job offers to the target group recruited. Such knowledge can help shipowner companies to effectively prevent the crisis related to the shortage of highly skilled seafarers and the subsequent disruption of the supply chain. In addition, it can also provide guidance for maritime universities to design academic programs customized to the expectations of both shipowners and future seafarers. Originality/value: Research dedicated to assessing the impact of meeting shipboard job requirements on seafarers' satisfaction and dissatisfaction has not yet been conducted. In addition, the paper makes an innovative attempt to confront the requirements for work at sea formulated by seafarers with the requirements of students as future shipboard employees. The survey used the Kano method, a management-specific method not previously used in the maritime industry. The addressees of the results of the survey can be maritime universities, shipowners and maritime industry employees. Keywords: Kano method, maritime industry, seafarers' requirements, students' requirements, 2 working on board. Category of the paper: Research paper

THE IMPACT OF BLENDED LEARNING APPROACHES ON THE QUALITY OF ENGLISH TRAINING AT UNIVERSITY LEVEL IN VIETNAM

This study investigated the impact of blended learning approaches on the quality of English training at Vietnamese universities, addressing a significant gap in understanding how blended learning is implemented in Vietnam's higher education context. The research aimed to explore implementation practices, identify challenges and opportunities, and develop recommendations for improving English language education through blended approaches. Using a qualitative case study methodology, the study collected data through semi-structured interviews with 20 English lecturers from eight universities in Hanoi, supplemented by 10 classroom observations and document analysis of course syllabi, learning materials, and institutional policies. The findings revealed that while blended learning shows promise in enhancing English language education, its implementation faces significant challenges including inadequate technological infrastructure, limited professional development opportunities, and inconsistent institutional support. Successful practices were identified in areas of assessment integration and online content development. These findings have important implications for educational policy and practice in Vietnam, suggesting the need for systematic improvements in technological infrastructure, professional development programs, and institutional support systems. The research provides valuable guidance for universities seeking to enhance their blended learning programs and contributes to the broader understanding of implementing blended learning in developing country contexts.

Review on Web Based IT Career Guidance System

Abstract: The future depends on what you are doing nowadays. Today, if a person does not have a clear idea of how and what correct path he should take to balance the present and the future, this is a cause for concern. Competition in the modern educational and professional world is at its peak. The importance of proper guidance for various colleges and work-related issues is another foundation for a better future. Nowadays, students are often faced with a dilemma when choosing a career. Students are confused about their career, which is the defining moment of their life. There are several factors that influence students' career choices, such as their personal skills, educational achievements and environment. We have a manual career guidance system guided by human advisors, but this system suffers from the following problems low number of human advisors, lack of advisors in many colleges, low number of advisors assisting students during their studies in colleges attend, and the position of college counsellors is so unpopular that students rarely meet with them for career advice. We were able to develop an online career guidance information system to solve problems related to a student's career. An online career guidance system was developed and implemented using data from various surveys and various research papers. The following languages were used: REACT, MONGODB, HTML, JavaScript, CSS, NODE JS, EXPRESS, BOOTSTRAP. OPEN AI APIS. The system was implemented and tested on 50 students and 76 of them found the career system very useful.

Measuring the Efficiency of Turkish Research Universities via Two-Stage Network DEA with Shared Inputs Model

The efficiency of universities, which have a network structure of production process, is an essential component of performance measurement in education. However, most previous studies use traditional Data Envelopment Analysis (DEA), which disregards the network structure of the production process in universities. This study adopts a two-stage Network Data Envelopment Analysis (NDEA) with shared inputs model to assess the overall, teaching and research efficiencies of Turkish research universities. The findings show that only 6 out of 23 research universities are efficient, and some universities with lower world rankings are more efficient than those with higher rankings. On the other hand, no significant difference was found between the efficiency levels of regions with a high level of socio-economic development and regions with a relatively low level of socio-economic development. The study also evaluates the effects of different priority scenarios on efficiency and the optimal allocation of shared inputs between sub-processes. This study provides guidance for universities seeking to improve their performance and for the Council of Higher Education (CHE) in determining incentives for research universities. It also promotes the use of multi-stage NDEA with shared inputs model over traditional DEA for accurate efficiency assessment in the field of education.

Challenges facing Arab researchers in conducting and publishing scientific research: a qualitative interview study

Arab researchers encounter formidable obstacles when conducting and publishing their scientific work. We conducted semi-structured interviews with 17 Arab researchers from various Arab Middle East countries to gain a comprehensive understanding of the difficulties they face in research and publication. We analyzed the transcripts using reflexive thematic analysis. Our findings revealed several key challenges. First, Arab researchers struggle to conduct high-quality research due to limited resources, inadequate funding, and a lack of a supportive research infrastructure. Furthermore, a shortage of teamwork and mentoring diminishes research productivity. Perverse promotion policies, heavy teaching loads, and low salaries force many researchers to seek external income sources, leaving them with insufficient time for research. Regarding publishing in high-impact journals, Arab researchers confront challenges existing of insufficient scientific writing skills, underrepresentation on editorial boards, and unconscious biases against researchers from economically challenged areas. Finally, achieving research integrity is closely tied to lack of access to essential resources. To address these issues, our participants proposed targeted interventions at the institutional and external levels. For example, universities can implement mentoring programs, offer workshops on scientific writing and publishing, and foster a supportive institutional culture for research. Addressing the underrepresentation of Arabic researchers on editorial boards is crucial for equity in global scientific publishing. In conclusion, acknowledging and addressing these challenges will empower Arab researchers, elevate research quality, and promote equitable global scientific collaboration. Our findings provide guidance for universities, governments, and international donors seeking to enhance research and publication practices in the Arab Middle East.

Defining and Advancing a Systems Approach to Achieving Educator Wellbeing: An Integrative Review of Wellbeing in Higher Education

Educators are crucial for student success in higher education, yet they often experience high levels of occupational stress which threaten their wellbeing. Informed by a conceptual framework initially developed for addressing worker wellbeing in the healthcare sector, another sector where workers experience high levels of occupational stress, this article explores how educator wellbeing is influenced by factors within the teaching environment, institutional environment and the external environment. Through an integrative review of existing literature, this article synthesises their findings to identify work system factors, individual factors, and outcomes and consequences of educator wellbeing across these domains. The resulting framework offers practical guidance for universities to identify, assess and respond to potential threats to educator wellbeing, ultimately enhancing the prospects of student success and meeting organisational goals without compromising the wellbeing of educators.

University Webometrics Ranking Analysis using SWOT and Gap Analysis

The Webometrics ranking serves as a crucial metric for assessing the quality and online visibility of universities. In this investigation, the study employs a SWOT analysis approach to delineate the strengths, weaknesses, opportunities, and threats influencing university Webometrics rankings. The primary objective is to scrutinize Webometrics rankings through the dual lenses of SWOT analysis (Strengths, Weaknesses, Opportunities, Threats) and Gap analysis. The approach includes collecting Webometrics ranking data from reliable sources, followed by an in-depth SWOT analysis to identify the factors that impact the university's position in the Webometrics ranking. Additionally, gap analysis is applied to assess disparities between the current Webometrics ranking and the university's aspirations. Through gap analysis, the study identified areas where the university has the potential to enhance its Webometrics standing. The study's findings are anticipated to offer valuable guidance for universities seeking to elevate their Webometrics rankings.

Machine learning prediction model based on enhanced bat algorithm and support vector machine for slow employment prediction.

The employment of college students is an important issue that affects national development and social stability. In recent years, the increase in the number of graduates, the pressure of employment, and the epidemic have made the phenomenon of 'slow employment' increasingly prominent, becoming an urgent problem to be solved. Data mining and machine learning methods are used to analyze and predict the employment prospects for graduates and provide effective employment guidance and services for universities, governments, and graduates. It is a feasible solution to alleviate the problem of 'slow employment' of graduates. Therefore, this study proposed a feature selection prediction model (bGEBA-SVM) based on an improved bat algorithm and support vector machine by extracting 1694 college graduates from 2022 classes in Zhejiang Province. To improve the search efficiency and accuracy of the optimal feature subset, this paper proposed an enhanced bat algorithm based on the Gaussian distribution-based and elimination strategies for optimizing the feature set. The training data were input to the support vector machine for prediction. The proposed method is experimented by comparing it with peers, well-known machine learning models on the IEEE CEC2017 benchmark functions, public datasets, and graduate employment prediction dataset. The experimental results show that bGEBA-SVM can obtain higher prediction Accuracy, which can reach 93.86%. In addition, further education, student leader experience, family situation, career planning, and employment structure are more relevant characteristics that affect employment outcomes. In summary, bGEBA-SVM can be regarded as an employment prediction model with strong performance and high interpretability.

Exploring the Student Perspective: Assessing Technology Readiness and Acceptance for Adopting Large Language Models in Higher Education

Digital technologies are changing and will continue to change how we learn and teach today and in the future. With the latest developments in the field of generative artificial intelligence (AI), particularly large language models (LLMs), the question of using AI-based tools in academic education is ruling the current discussions about the transformative impact of AI in higher education (HE).
 These discussions range from banning these technologies for learning and teaching in HE to guided study support. This study avoids taking up these multifarious and partly controversial debates. Instead, we show how students perceive using AI-based tools for automated text generation for their studies. Drawing on a synthesis of two theories: the 'Technology Readiness Index' (TRI) and 'Technology Acceptance Model' (TAM). The model is validated based on survey data collected among undergraduate first-semester students (N=111) of a computer science-related study programme in Germany in winter 2022/23. The students had to evaluate their relationship to that new technology focusing on their readiness for technology adoption and acceptance. By analysing the collected data with a partial least squares model, we find that the optimism toward the new technology positively influences technology acceptance, while discomfort with the technology negatively influences perceived ease of use. The paper concludes with recommendations for action for adopting LLMs in HE. A proper investment in building AI skills in academic teaching plays a valuable role in fostering the students' positive attitude and innovativeness towards this new technology. Additionally, there is a need for more education about the risks and challenges of using this technology to reduce the impact of factors such as discomfort on ease of use. This requires a factual discourse, away from the current hype-induced exaggerated and hyperbolic statements, for instance, in developing formal guidance for universities.

Implementing e-learning environment at universities in Bosnia and Herzegovina

The ubiquity of e-learning has necessitated research into its application and effectiveness. This study scrutinizes the factors influencing e-learning adoption in Bosnia and Herzegovina, specifically within the higher education sector. To determine these influential factors, the study surveyed professors from both private and public universities via emails, achieving 220 responses from over 1,500 sent. The collected data was analyzed using SmartPLS, and regression modeling was used to determine the significant relationships among the factors. The findings highlighted seven key elements, including e-learning policies, institutional readiness, quality e-learning systems, course design quality, awareness of benefits, interactive discussions, and motivation. Furthermore, the research unveiled six substantial gaps in the current e-learning structure: resource insufficiency, lack of e-learning skills, ineffective course design, inadequate knowledge of benefits, low motivation, and a lack of student-centered learning. It has been concluded that these seven factors, and their intricate relationships, significantly impact the successful adoption and effectiveness of e-learning tools within universities. The research offers practical guidance for universities aiming to implement or enhance e-learning practices, emphasizing areas requiring increased attention and resources. It underscores the importance of not only the technical infrastructure but also the quality of course design, the role of awareness and motivation, and the necessity of a student-centered approach.

University-as-a-service: Designing thinking approach for Bangkok University business innovation curriculum and service development

ABSTRACT This study explores the implementation of the university-as-a-service (UaaS) paradigm in higher education. Through qualitative research, it examines student and stakeholder experiences to inform the redesign of university programmes. The UaaS model aims to enhance university engagement with the business ecosystem and meet the demands of the digital economy. Services within the UaaS framework include research, international programmes, sustainable development, consulting, Center of Excellence establishment, and startup support. The study highlights the importance of developing an action plan and prioritising tasks, balancing collaboration and customisation. Integration of Design Thinking principles is crucial for equipping students with essential skills. Aligning university programmes with the evolving needs of the digital economy is emphasised. This research provides practical guidance for universities to enhance their engagement, fostering economic growth and social progress. Future efforts should refine and optimise the UaaS framework.

THE ROLE OF ACADEMIC ADVISORS IN SERVING GUIDANCE AND COUNSELING FOR STUDENTS IN HIGHER EDUCATION

This research was conducted based on empirical findings which showed that the problem was the low level of guidance and counseling services for students to academic supervisors in universities. Therefore, it is necessary to know clearly in responding to the situation, so that the problem lies where, whether it is because of their ignorance or their lack of understanding of the existence of guidance and counseling services in universities. This study aims to determine the role of lecturers in guidance and counseling services in universities. The method used in this study is a descriptive method in the form of survey research. The research subjects are lecturers and students of the primary school teacher education study program for the 2021/2022 academic year. Based on the analysis of the data in the study, it can be concluded that the role of lecturers in guidance and counseling services is in the fairly good category.

EUR-ACE accreditation for chemical engineering in Spain: Current situation, lessons learned and challenges

The accreditation of engineering programmes is a subject of great interest in the last decades. However, most studies in the literature are focused on case studies or deal with the different levels of acceptance of the groups involved in the accreditation. There are two main approaches for the accreditation of engineering programmes, i.e., at national or international level. Whereas most developed countries have established national standards for the quality assurance of the university studies, international accreditation systems for engineering studies are limited to 3 alternatives. The interaction between national and international accreditation systems is poorly understood despite of their significance in the design and management of the programme. We aim to fill in this gap and provide useful guidance for universities aiming to apply for the EUR-ACE® label in their chemical engineering programmes (bachelor or master). In general, there is a high level of complementarity between the Spanish and EUR-ACE accreditation systems. However, there are still challenges. For instance, the ad hoc procedure proposed by the national accreditation agency in Spain does not fully consider chemical engineering as a traditional branch of engineering. In addition, the changes in the Spanish accreditation system might negatively impact the current ad hoc procedure for EUR-ACE accreditation for some universities. The incorporation of IChemE in the accreditation process would be an option to deal with this issue.

Management of Religious e-Counseling at Islamic Religious Colleges in the New Normal Era

<p class="06IsiAbstrak"><span lang="EN-US">The existence of technology requires us to change in all aspects of life, including guidance and counseling in Islamic religious colleges. Maximum utilization of resources in Society 5.0 benefits the effectiveness and efficiency of managing guidance and counseling services. This study aimed to identify the management of religious e-Counseling at Islamic Religious Colleges in the new normal era. This research uses qualitative research with case study analysis. The research subject is UIN Sunan Gunung Djati Bandung. The results showed that implementing e-Counseling at UIN Sunan Gunung Djati Bandung was the responsibility of the Unit of Psychology Service. Clients can access the process of implementing e-Counseling by contacting the registration admin, then the admin will contact the psychologist/counselor and inform the client/counselee about the counseling schedule with the psychologist/counselor. Clients/counselees can also follow the counseling process according to the agreement and procedures set by the Unit of Psychology Service of UIN Sunan Gunung Djati Bandung. Handling problems in e-religious counseling is carried out through stages: opening: awareness planting (<em>qawmah</em>), exploration stage (<em>taubah</em>), contemplation stage (<em>muhasabah</em>) and basirah (determination of vision and goals), implementation and development stage (‘<em>amal</em>) and the prayer stage (closing) with transpersonal approaches such as prayer, fasting, dhikr, and Islamic art therapy.</span></p>

Guidance and Counseling In Higher Education

The purpose of writing is to describe the availability of guidance and counseling facilities and infrastructure in universities. One of the successes of guidance and counseling services is supported by adequate infrastructure facilities. This study technique uses a literature review or library research. The conclusion is that guidance and counseling services in universities have orientation services, information services, placement and distribution services, content mastery services, individual counseling services (individual), Group Guidance and Group Counseling services, Group Guidance (BKp), and Group Counseling (KKp). consulting services, mediation services, and advocacy services. and assistance services provided to students include providing guidance assistance in personal, social, study, and career fields.

A study on the multidimensional driving mechanism of cross-regional scientific collaboration network in China

ABSTRACT Multidimensional proximity has been considered the important factor affecting regional scientific collaboration network (RSCN) and has received extensive attention from scholars. This paper constructs a cross-RSCN based on co-authorship across 31 regions in China, incorporates traditional multidimensional proximity and network embedding proximity into a unified framework and proposes a five-factor driving model for dissecting the mechanism of cross-regional scientific collaborative innovation (CI). The results show that the scientific collaboration network is gradually becoming saturated with connections, and the polarisation of cross-regional collaboration is increasingly serious. The collaboration intensity is affected by the co-movement of several proximity factors, among which geographic proximity (GP) is the main but not the sole one that positively affects the cross-regional scientific collaboration. Based on the decision tree model, we conclude that structure proximity may compensate for low GP and low economic proximity (EP) on cross-regional CI performance. The positive effect of network location proximity on regional scientific collaboration is more sensitive when the EP is not high. The findings provide significant guidance for scientific research institutions, universities and regional policy-makers to select appropriate partners as well as network embedding strategies, and further contribute to long-term improvement of scientific innovation performance and stable regional economic growth.

Improving the Effectiveness of Career Guidance in Universities: Marketing Approach

The development of the country is directly related to the quality of higher education. In times of active development of information technologies, increasing the availability of information resources and their accessibility, the problem of choice as such is acute. The complexity of the choice is especially acute at the time of choosing a future university and specialty. In this context, it becomes relevant to study the effectiveness of communications between the university and applicants, and a set of standard for universities, career guidance activities. The purpose of our research is to identify the most effective communication channels between the university and applicants in order to assist the last ones in choosing a university and specialty. The research methodology is based on marketing tools using a systematic approach. The scientific works of Russian scientists in the field of marketing research and the results of surveys of students of Baikal State University (BSU) conducted by the authors served as an informational and empirical basis. The scientific novelty consists in the systematization of communication channels in terms of their relevance and taking into account the transmitted information when deciding on admission to a university and choosing a specialty. The article describes the results of studies of the effectiveness of career guidance measures on the example of BSU. The conducted research made it possible to identify the most popular career guidance activities and to identify the motivational mechanism for choosing a university and specialty.

A Multiperspective Intervention Path Study of Employment Expectancy in the Era of Big Data

The increasingly large employment group in colleges and universities has brought huge employment pressure to the society. Therefore, improving the level of professional ability of college students, providing students with personalized career development direction planning, and helping students to establish a correct concept of career selection are feasible ways to solve the structural contradiction of college students’ employment. The arrival of big data era provides new development opportunities for employment work in colleges and universities. Big data drives the high-quality development of precise employment in colleges and universities, which is inevitably required to reach the precise requirements of work development, information mastering, platform docking, information pushing, and help work. The traditional employment guidance work is backward in means and poor in timeliness, which leads to poor intervention effect on students’ employment expectation. With the deepening of digital campus construction and the development of big data technology, massive educational data has been accumulated but not reasonably utilized. Therefore, in this paper, we take the massive student data accumulated in digital campus as the research object, based on the research method of convolutional neural network, to explore the hidden personalized information of students behind it, predict their future career development direction, and provide scientific and technological support for the work of university education and teaching. Thus, the architecture classical DenseNet was improvised to avoid gradient disappearance and guarantee the classification accuracy, thereby targeting to reduce the number of connections. The study also proposed a 2-DenseNet model, wherein the attention module was embedded into 2-DenseNet followed by the conduction of training and validation on the university employment dataset. The experimental results show that the method proposed in this paper could predict the appropriate career development direction timely and effectively based on multiple perspectives of students’ comprehensive quality. This would enable the students to plan and adjust their employment expectations leading to disseminating of efficient employment guidance in colleges and universities.