Conceptualizing Data Driven Decision Support Component in Academic Information Management System

The increase in demand for the completely automated system to manage all the academic activities intensifies the need of an efficient information management system. The Academic Information Management System (AIMS) is an attempt to automate the functionalities of a college or university academic systems. In this system, the users are allowed to perform fully flexible operations. Both students and faculties are allowed to register, login, registration, approval of the project, marks entry, attending the quiz online, uploading and downloading of files and scheduling of class slots. Keywords: academic, information management, scheduling, slots, quiz, flexible, automated

this system is design to complete the digital management of students' result files in middle schools' daily education work. The system focuses on conform the business process to the operation, and strives for comprehensiveness and versatility, making the system not only applies to one education organization. The combined method of life cycle approach and prototyping are adopted on the choice of development methods, which follows four phases, including research, analysis, design and implementation of the system to carry on the design. And in the detailed design, evolutionary prototyping is adopted. With the deepen understanding in the using, afresh analysis, design and implement one part or several parts will be processed. Finally through the test, this system has reached the design requirements of various functions, and achieved the expected design goal.

One of the important features of the “new information age” is “big data”. In the age of big data, with the introduction of student information management systems, colleges and universities are increasingly paying attention to systematically managing student information management and improving their efficiency, effective management of student information and innovative development to build a new model of management system. In studying the evolution of student information management, big data technologies emerging in the information age play an important role. By leveraging big data to improve systematic management of student information, colleges and universities can manage student information faster and more efficiently and make new contributions to the advancement of student information management. In this article, information management is considered as the theoretical basis for research, big data technology is used as the main search algorithm, and its important content is combined to analyze and study the possibilities of the student information management system. In this article, an information management system for university students is used as a research object, which is optimized and improved through big data technologies. Big Data technology can be seen as a kind of algorithm for analyzing and processing data. Therefore, it can be used to create a student information management strategy. The experimental results show that this research has a better impact on the creation and implementation of an information management system for students using Big Data technology and the application of Big Data technology in the information management system for students.

With the advance of education informationization in china, information technology and data mining technology has been widely used in the field of education. The decision tree method is one of the data mining methods; it does not require any assumption, can intelligent classification to a large amount of data directly. According to certain rules to find hidden and valuable information.Use the idea of learners as the center as guiding principle, using decision tree algorithm of data mining technology to build student information management system, selects typical C4.5 algorithm among the decision tree methods, Take mass information about employment of graduation in university students' information management system as an example to generate the decision tree, collect potential rules and factors in favor of graduat employment, so as to guide the education and management.

An overview of the concepts and activities of Integrated Academic Information Management Systems (IAIMS) at U. S. medical schools is presented and the future of the library is discussed on the basis of the Matheson's report. The prototype program of IAIMS, which was proposed by the U. S. National Library of Medicine, is being introduced in three phases. The strategic planning of four medical centers where IAIMS projects are being implemented is compared; that is, Georgetown University, University of Maryland, University of Cincinnati, and Johns Hopkins University. Lastly, the feasibility of introducing the IAIMS concept to medical libraries in Japan is discussed.

A design of Student Information Management System (SIMS) is vital research that has a specific part in encouraging growth of students. However, an effective design of SIMS is a challenging thing that is essential for every university to manage student's information. To overcome this to design a student information management system by Machine Learning (ML) based Levy Flight technique with K-means clustering algorithm (LFK) is proposed to design a management system. The goal of this system is to help teachers to understand fully about learning thins and adapt to students' skills by Browser/Server (B/S) system. Initially, the student data is analyzed and system function module is included to SIMS. Then, an optimal k value is determined by inner and outer distances which sets a total range. The experimental results show that proposed method achieved accuracy of 95.36% which is greater than existing models such as K-Means Clustering and Logistic Regression (LR).

A software platform called an Academic Management System (AMS) is created to handle the academic operations of educational organizations like colleges, universities, and schools. To handle student details, attendance, fees, grades, performance, and course content/exam modules, the system provides a number of modules. Administrators and instructors can handle student data like personal information, contact information, and academic records using the student profile administration module. Students can seek a leave of absence through the leave request administration module, and instructors can accept or reject these requests. Parents can watch their child's scholastic data, including attendance, fees, and grades, through the parent-viewing module. While the fees management module tracks student fee payments and enables administrators to create fee reports, the attendance management module tracks student presence and gives reports on student attendance. Teachers can input student scores for tests, quizzes, and examinations in the mark administration section, which also produces reports for parents and managers. Grades, attendance, and instructor feedback are all included in the student performance management module's complete perspective of student success. Administrators and instructors can compare student performance across courses, assess student performance over time, and pinpoint areas for growth using the performance analysis tool. The graphical reports section presents student achievement data in graphical form, enabling managers and instructors to spot trends and patterns right away. Administrators and instructors can create reports and progress cards for specific students or complete classes, download them, and then transmit them to the students or classes in question. Teachers can submit course materials, such as lesson notes and readings, and handle test schedules and modules using the course content/exam module administration module. Overall, an academic management system aids educational establishments in successfully and efficiently managing their academic activities. It also enhances interaction and cooperation between educators, administrators, students, and parents. KEYWORD: School, Admission, Management, Students, Parents

Peasant agroecology faces limitations in commercial visibility and institutional recognition despite its contributions to ecological, food and cultural sustainability. This article analyses the participatory construction of a territorialised collective brand within the Red de Soberanía Alimentaria de Productores Indígenas de la Montaña de Guerrero, Mexico (SAPIGro), and systematises the Territorialised Collective Brand Model (TCBM). The research was conducted in 2024 with 18 families from seven rural Indigenous communities using a participatory action research strategy that combined symbolic co-design workshops, participant observation, documentary analysis and Frederic Vester’s systemic analysis matrix to identify critical variables within the local agri-food system. The results show that the TCBM is structured around four interrelated dimensions: identity, organisational, productive and commercial–symbolic. Cultural identity operates as a regulatory variable, while organisational capacities and market access constitute critical variables. The collective brand functions as a social innovation and symbolic territorialisation mechanism that strengthens community agency, revalues Indigenous agroecological food systems, and provides transferable methodological inputs for rural development policies and strategies grounded in territoriality and solidarity-based economies.

Photovoice research is conducted by researchers to communicate images or photographs, and it has high confidence in analyzing the value, story or meaning of an image. Several previous studies that examined photovoice as a research strategy were analyzed and reviewed. This systematic review used an article selection process. It was defining the purpose, conducting a literature search, pulling articles by reading abstracts, reading the full paper, data abstraction, and conducting an analysis. The photovoice article selection was classified into education, health, and social science domain. Finally, forty-one articles have been reviewed with the total of participants involved ranged from five to fifty individuals. The majority of research method in the articles was participatory action research (PAR) through qualitative inquiry or field visits. Meanwhile, the research instruments used photography, documentation, observation, and interviews. In various fields of research, photovoice is able to increase the understanding of individuals or groups to interpret the content of an image or photo.

Software bugs discovered by end-users are inevitable consequences of a vendor’s lack of testing. While they frequently result in costly system failures, one way to detect and prevent them is to engage the customer in acceptance testing during the release process. Yet, there is a considerable lack of empirical studies examining release management from end-users’ perspective. To address this gap, we propose and empirically test a release framework that positions the customer release manager in the center of the release process. Using a participatory action research strategy, a twenty-seven-month study was conducted to evaluate and improve the effectiveness of the framework through seven major and 39 minor releases.

Since the needs for academic management are always changing, the creation of academic information systems must focus on user benefits and satisfaction in order to gauge how successful academic management systems are. This research uses the Delone and McLean IS Success Model which is known as one of the system success models, so the aims to ascertain the effects of system, information, and service quality, as well as usage rate, on benefits and user satisfaction SIAKAD system. Respondents were determined using the Slovin formula and taken using proportionate stratified random sampling techniques as many as 100 people. Descriptive analysis was carried out to explain respondents' perceptions and evaluate the success of the system using Three levels of communication were used to measure the success of the system: technical, semantic, and effectiveness levels. The Delone and Mclean IS Success Model's variable relationships were investigated using SEM-PLS analysis. Hypothesis testing results indicate that User Satisfaction is significantly impacted by Information; System; and Service Quality, then Information Quality also significantly affects Usage; and Net Benefits are significantly impacted by User Usage and Satisfaction; however, neither System Quality nor Service Quality significantly affects Use or Use on User Satisfaction.

The re-establishment of the East African Community (EAC) necessitated the need to establish various institutions required for proper implementation of the harmonization pillars (Customs Union, Common Market Protocol, Monitory Union and Political federation) within various sectors. For example, the Inter-University Council for East Africa (IUCEA), a surviving institution of the EAC was tasked to lead the harmonization of education and training system in East Africa (IUCEA, 2009). The IUCEA has set up various frameworks and programs to achieve this mandate, however IUCEA has not yet established a one stop live data system on Universities and Programs which would provide for evidence-based policy process. This study therefore leads to an establishment of an Academic Programs Information Management System (APIMS) which breaks the ground for an established regional system on Universities and Programs offered with in the East African Community. The application was developed using Django Web Framework and validated with 15 IUCEA staff. The established system will promote Students and Staff Mobility and also protect students against degree mills.

Currently, a learning management system (LMS) plays a central role in any e-learning environment. These environments include systems to handle the pedagogic aspects of the teaching–learning process (e.g. specialized tutors, simulation games) and the academic aspects (e.g. academic management systems). Thus, the potential for interoperability is an important, although over looked, aspect of an LMS. In this paper, we make a comparative study of the interoperability level of the most relevant LMS. We start by defining an application and a specification model. For the application model, we create a basic application that acts as a tool provider for LMS integration. The specification model acts as the API that the LMS should implement to communicate with the tool provider. Based on researches, we select the Learning Tools Interoperability (LTI) from IMS. Finally, we compare the LMS interoperability level defined as the effort made to integrate the application on the study LMS.

An Academic Management System (AMS) is a technological tool used to manage academic processes in educational institutions. AMS helps optimise resources through data management, but it has information security challenges. Due to the need to inspect security in an AMS, this study aims to identify and evaluate risks and improve controls for AMS security. Adhering to international standards like ISO/IEC 27001:2013 is important for addressing cyber threats. The case study focuses on the AMS of the Technical University of Manabi, focusing on confidentiality, integrity, and availability of information. The methodology involves analysing AMS information security components using surveys conducted with the institution’s data centre personnel to determine the current system status. The results show that there are 48 active controls and 33 inactive ones, meaning that the AMS is partially protected according to the standard. Additionally, risks associated with likelihood and impact are identified, along with recommendations to strengthen AMS security management.

The subject of this research, documental and qualitative, is the evasion of students in technological courses of higher education. The research is justified by the fact that there is still a little explored field of knowledge about avoidance in higher education. The main objective of this study was to identify the factors that caused student dropouts at the Federal Institute of Sao Paulo (IFSP) in a campus from 2011 to 2017. Institutional documents were examined regarding 746 students who had been evaded. The results showed that, in spite of the different actions developed by the institution to know the reasons and avoidance, these were not considered satisfactory by the participants of the research. The causes pointed out by the subjects interviewed can be classified in: a) Scarce commitment to avoidance; b) Organizational failures (limitations in the academic management system and absence of standardization for collection and analysis of data on avoidance); c) Failure in the relationship between sectors.