The selection of a suitable university is an important decision for different people. Their decision is based on a number of factors such as research environment, student strength, geographical location, course selection, and the overall ranking of the university. These requirements are normally followed by surfacing across the search engines/web portals, with different query strings and having hundreds of thousands of pages which further require manual inspection. Recommender systems: Today, there are numerous recommender systems accessible in many different fields that make it easier for people to go about their daily lives. Information visualization techniques: Information visualization is a strategy for presenting data in a meaningful and illustrative manner that people can readily analyze and comprehend.
2.2 Visualization Techniques
The authors [12] explain that WWW is currently experiencing revolutionary growth due to various emerging tools, techniques, and concepts. In this paper [13] the author also discovers and gives the solution to the problems while using an emerging Web 2.0 technology and he explores the application of mashups for the Journal of Universal Computer Science (JUCS) and encourages the readers, and authors to use that application. There is continuous improvement in Electronic journals and their services based on technological developments. Great effort has been made in providing high-level access options to the users of e-collections using 2D or 3D maps involving the semantic analysis and visualization of relevant topics [14]. Some important aspects of modern digital libraries like searching intelligently, to visualizing the search results, have been discussed in [15]. The author expands the publication of J.UCS and it is necessary to know about the current state of readership and accessibility of journals the author also determines which locations (cities and institutes) are contributing less, more, and which have stopped contributing [16]. Many universities developed web-based campus maps [20]. The spatial features of the geographical information system (GIS) are added in such types of maps for facility visual searches. The author discussed that the purpose of this paper is to design and build up an interactive, easy, and web-based Beytepe Campus Map to process visual queries on the geographical information system (GIS) and make it available through the Hacettepe University website, the main categories have also sub-categories to present the places at Beytepe Campus 1) Academic units,2) Administrative unit, 3) Sheltering, 4) Nutrition, 5) Health, 6) Transportation, 7) Entertainment, and 8) sports center. The author discussed Vimo in the integrated comparison portal released in January 2006. Vimo allows US rates, and purchases health insurance and health saving accounts, and also selects the physician profiles from across the US. Vimo can find physicians and compare prices of each hospital and also there is a facility to allow the users to read and post reviews. The author uses Google Map API which searches the exact location of a health professional’s office when the consumer clicks on the name of Google Map, Health map brings different data sources together to complete a combined and comprehensive view of the present state of infectious diseases and also the effect of these diseases on human and the effect on animal health. Google Maps also provide the latitude and longitude to show the exact hospital location and address but the author has not mentioned here about which hospital is better than the other hospitals. The author [16] explains that JUCS is a unique electronic journal of computer science having more than Fifteen hundred (1500) research publication in different domains of computer science and added so many new ideas and features recently, which includes semantic searching as well as annotative option and collaborative option. JUCS is 1st electronic journal that implemented personal annotations and public annotations. JUCS also implemented research publication in multi-format options and define the category in multiples way etc. The author [17] also explored the distribution of authors who published papers in JUCS and editors across the world. Moreover, JUCS keeps up all the data for authors and editors which includes their country information, city information, and university information. The author 1st developed two (02) types of options. In 1st option visualization of author information with JUCS data on Google Map API. 2nd visualization of author distribution geographically and the Zooming option is also available. For full visualization, the author used manual effort and somewhere updating blank files for all this to be more effective automated technique is very much necessary. While using automated techniques one can better explore the city name and country name of the university in the search query Google Map API with author information. There is no comparison among authors, that shows users about the author’s publication that in which area he is so strong and how many publications he did in that category etc. Cartography [18] is the word used as the art and science of making maps and historically used by Geography as its language from this cartography gained new tools and media that enhanced the static maps and introduced multiple layers. The term Geographic Visualization or “GeoVisualization” (Gvis) refers to spatial data and can be used for all layers of problem-solving in geographical analysis. In the paper, the author presented two applications of Google Maps API in which health and higher education data overlaid as a thematic layer on top of the standard Google Maps base layer. The Data used to generate health applications result from registered patients within 48 General Practices in Southwark Primary Care Trust, situated in the region of Southwark, South London. These data are together through a system called Exeter and are used to monitor the practice activity against the Quality and Outcome Framework (QOF). The data used within the Higher Education (HE) mashup use an extract of the Universities and Colleges Admissions Service (UCAS) applicant database which was created during the 2004 application cycle. The author also discussed the advantages of data visualization and how to use different colors, fonts, and layouts while using data visualization techniques and with the help of data visualization, users avoid potential pitfalls [13]. The author explained that the Convenience store area is dependably the important feature, which is additionally a vital factor. Appropriate stores cannot just decide the number of store customers, numerous elements decide the accomplishment of a convenience store, and the nature of the store address assumes a key part in the achievement of the accommodation store. The author presented data visualization innovation and data recovery innovation in light of the investigation of the innovation of data visualization and geographic spatial metadata [14]. The creator additionally said that shading and geometry portrayals are quickly perceived by the human’s cerebrum, and information representation advances furnished by information mining come about with characteristic and natural activity interfaces. The fulfillment of the client’s request for such huge numbers of information mining emphasis was performed. The examination is as yet progressing and he is constantly upgrading and creating basic information mining calculation and information representation models in the framework [10]. The author discussed that the visualization technique is not a new concept but by using data visualization one can present the data graphically or pictorially and also discussed the free sources of data and the requirement of user-created content on social media have also led to rise in popularity of data visualization concept. The author also discussed the advantages of data visualization and how to use different colors, fonts, and layouts while using data visualization techniques and with the help of data visualization, users avoid potential pitfalls. Librarians and other information professionals are using data visualization to generate annual reports and insightful internal library appraisals. Library staff can also prepare themselves to teach and assist others in creating captivating data-driven visualization [19].
2.3 Decision Support Systems
The expansion of schools and the increasing number of campuses, departments, teachers, and students call for the development of an open and efficient online school administration system. The current resource management platform poses challenges for sharing educational resources due to its varied structures. This study [21] proposes an information integration platform based on Service-Oriented Architecture (SOA) to unify various enterprise application systems, enabling information sharing and meeting cross-departmental business needs. The proposed platform minimizes the impact of demand changes, enhances flexibility, and streamlines educational administration processes. By adopting SOA and Web services, the platform integrates existing information system resources, saves development costs, and improves performance management quality. The loosely coupled and reusable module design allows for seamless integration and reduces development complexity. The use of Web services technology simplifies system deployment and usage. It is expected that as the support for SOA advances, this SO-based information integration platform will find broader applications in enterprise informatization.
In this paper, the author [22] explained that technological advances necessitate collaborative efforts among universities, teachers, and students to restructure departments and courses. Failing to do so risks reduced quality and competitiveness. To address this, a decision support system is proposed with three stages: data collection, conversion into meaningful information using natural language processing, and ranking alternatives using multi-criteria decision-making. This system benefits universities by informing department and course offerings, helping teachers create or shape courses, and guiding students in their choices. Experimental validation using computer engineering job postings and course contents from Turkish universities confirm the system's applicability and reliability.
This study [23] focuses on developing an online learning support system using location-based service architecture. The research analyzes learning result data and implements an improved algorithm to enhance accuracy. The study concludes that the learning support service system plays a role in improving the quality of online education and advancing its development. By combining location-based service architecture with the learning system, the study introduces a new research direction. The algorithm improves content-based recommendations by incorporating weighted recommendation results based on geographic information, location preferences, and user decision-making. The system tracks students' real-time progress, provides personalized guidance, and effectively monitors learning progress and proficiency. The evaluation system considers students' achievements and abilities, offering scientific and personalized service. The learning support system employs big data, learning analysis, and mobile Internet technology to provide intelligent and humanized support services, while the application of location-based service architecture introduces a new evaluation and teaching method, quantifying learning states and reflecting learning effects comprehensively and objectively.
The article [24] addresses the concern of low graduation rates at four-year state colleges, despite the use of academic indicators in the admission process. The authors suggest using an ensemble of analytic models that incorporate cost analysis to inform decision support systems. By analyzing ten years of data for 10,000 students and applying ten different models, the research aims to identify the best predictor of at-risk students. The study also utilizes the receiver operating characteristic curve to determine the optimal balance between false positive and false negative levels to achieve cost-effectiveness.
This paper [25] focuses on analyzing students' physical education information, course exam results, and learning data from an online teaching platform using the forest algorithm and decision tree algorithm. The objective is to generate decision trees and classification rules to identify factors influencing students' physical education performance. By constructing a model for assessing teaching effectiveness, the study aims to improve teaching quality and strategies. The research includes data collection, preprocessing, model construction, algorithm optimization, and simulation results. The CART algorithm is specifically applied to analyze student data and predict their effectiveness in physical education. The study highlights the importance of effective teaching methods in e-learning platforms and suggests pedagogical adjustments based on the identified rules. Decision trees and random forests are chosen due to their clarity, simplicity, computational efficiency, and accuracy. The application of CART algorithms in assessing student effectiveness in physical education holds significance.
This paper discusses [26] the separation of decision modeling from process modeling and introduces a Decision as a Service (DaaS) layered Service-Oriented Architecture (SOA). The DaaS approach treats decisions as automated and externalized services that processes can invoke on demand. The paper formalizes the DaaS framework using Decision Model and Notation (DMN) constructs and evaluates its adherence to SOA principles such as abstraction, reusability, and loose coupling. The benefits of the DaaS design on process-decision modeling and mining are discussed, and a real-life example of a bank loan application and approval process is used to illustrate the DaaS design. The paper contributes to the understanding of the interaction between decisions and processes and demonstrates the scalability, maintainability, flexibility, and understandability provided by the DaaS design. The proposed framework enhances integrated process-decision modeling and shows promising results in real-life event logs.
The importance of successful internships for students' future careers is recognized, and a decision support model is proposed to enhance the assignment process in higher education. The model consists of seven phases, which can be extended to nine phases, including students' choice of internship place. The model is iterative and interactive, involving the course coordinator and students. Results from four scenarios validate the model, showing a high correlation between students and internship proposals. The proposed decision support system aims to complement the manual assignment process, which becomes challenging with a large number of students and proposals. The model incorporates objective and subjective evaluation elements to improve student and company satisfaction. However, limitations include the inability to measure the impact on student employability and the difficulty of quantifying soft skills. The model requires further testing in different scenarios and institutions [27].
This study examines [28] the role of estimated risk in educational choices and its impact on educational inequalities, specifically focusing on social background differences. Using data from the ISCY Project in Barcelona, the study analyzes the estimated risk in higher education access. The findings reveal disparities in estimated risk based on social and economic factors. By operationalizing and contrasting the concept of estimated risk, the study demonstrates its usefulness as a framework for explaining educational inequalities and evaluating educational policies. Students' educational choices are influenced by their social background, leading to educational segmentation and the potential reproduction of social inequalities. The study explores the role of risk management in educational choices, considering factors such as motivations, academic abilities, and resources. Survey data are used to operationalize economic, academic, and social risks estimated by students and examine their relationship with actual choices.
Despite the ongoing concern about graduation rates at four-year state colleges, little improvement has been made in overall graduation rates. Academic indicators like high school GPA and ACT/SAT scores have long been used for selective admission, yet recent statistics indicate that less than 40% of students graduate within four years in the US. To address this issue, the authors propose an ensemble of analytic models that consider cost as a more effective approach for decision support systems. The study [29] analyzes ten years of data for 10,000 students and applies ten analytical models to identify at-risk students. By using the receiver operating characteristic curve, the research determines the optimal balance between false positive and false negative levels. Implementing a decision support system with predictive analytics can help identify at-risk students early on and implement interventions to prevent dropout. This approach enables administrators to make cost-effective decisions and utilize limited resources efficiently. By focusing on first and second-semester dropouts, timely decision-making and assessment of the effectiveness of administrative changes can be achieved. The article concludes with discussions and recommendations on modeling and practical applications within resource constraints.
The paper [30] proposes an approach to building configurable service-oriented decision support systems through automated service composition, which simplifies the development process. The results presented include a functional framework for different types of decision support systems, requirements for configurable service-oriented systems and their components, and a conceptual model for such systems. This novel approach enables the development of problem-specific decision support systems that can be used with little or no special training, accelerating the development cycle. Future work involves encoding typical service compositions and creating a methodology for generating services as building blocks in these systems.
A decision support system was developed to assist the community in selecting a suitable college based on their capabilities and job demands. The system uses the Simple Additive Weighting (SAW) method to provide recommendations to users by considering predetermined criteria. The study [31] concludes that SAW is effective in solving the selection of universities problem, with accreditation being the most prioritized criterion. Suggestions for further improvement include exploring other decision-making methods, incorporating additional criteria, and utilizing a computer application to streamline the decision-making process.
Automating and optimizing the creation of timetables for educational institutions is crucial to reduce costs. Previous studies on this problem have been based on unrealistic models with limited practical application. This paper [32] summarizes the work by Bullet Solutions, which focused on understanding and modeling the problem, developing robust algorithms, and employing optimization methods. The BTTE application, resulting from this work, achieved high-quality results with significant time savings (85%) in all analyzed cases. The application improved processes, centralizing and organizing information, increasing workflow efficiency, and aligning institutions with digital society procedures. The use of advanced technology for automation and optimization has enhanced the image and positioning of institutions while providing top management with greater control over teaching services. Notably, considerable savings in teacher hiring have been realized through the implementation of the BTTE application.
A study [33] was conducted to develop a Data-Driven Education Decision Support System (DDEDSS) as an innovative tool for educational decision-making. The DDEDSS software prototype was designed and tested using education data from two sessions. The system successfully evaluated learners' performance and provided a basis for curriculum optimization and class adjustments. The research demonstrated the significance of DDEDSS in educational research. The study focused on data acquisition, storage, integration, analysis, and mining, using SQL Server 2008 as the tool software. However, the development of the DDEDSS software faced challenges in utilizing built-in data analysis and mining functions. The study also identified the alignment between the five levels of data processing and the subject system's levels of practice, technology, science, sentiment, and philosophy, further validating the feasibility of the information and interaction system.