Academic Planning Research Articles

Korupsi dalam Perspektif Al-Qur’an

This study aims to analyze the role of the head of the Madrasah's academic supervision in improving the performance of teachers at MTs Darurrahman Rimbo Bujang, Tebo Regency. The research method used is qualitative with a descriptive approach, where data is collected through in-depth interviews, observations, and document analysis. Interviews are conducted with the head of the Madrasah, teachers, and other educational staff to gain a comprehensive understanding of the academic planning and supervision processes implemented. Direct observations of teaching and learning activities, along with document analysis of the work plans, are carried out to delve into the implementation of planned programs. The findings indicate that the head of the Madrasah's academic planning is crucial for enhancing teacher performance. The head of the Madrasah develops a structured plan involving all relevant stakeholders, setting clear goals, and planning periodic training programs. The implementation of academic supervision is conducted through a collaborative approach, where the head of the Madrasah and the supervision team provide constructive feedback to teachers following direct classroom observations. The follow-up of the supervision is also a critical aspect, with a report on supervision results being prepared and regular meetings held to evaluate teachers' progress. With this follow-up, it is expected that teachers receive the necessary support for ongoing development, creating a culture of reflection and continuous improvement in the learning process.

Legal frameworks and state policy in education: A theoretical analysis

The analysis of the concept of "state policy in the field of education" highlights the necessity to prioritise the issue of avoiding and eliminating the problem of social diversification in the provision of educational services. This process can be seen as strategic academic planning. Furthermore, the Constitution guarantees the right to participate in primary, secondary and higher education, respectively, which is an absolute right for all citizens. It also imposes an obligation on the state to ensure the structuring of educational services. In the course of composing this research article, the following general scientific methods of cognition were employed: analysis of literature sources, systematisation and generalisation methods. In the course of writing this scientific article, the following general scientific methods of cognition were employed: analysis of literary sources, and the method of systematisation and generalisation. To assess the efficacy of methodologies employed in the analysis of legal support for state policy in education, a survey was conducted among 27 legal scholars. Responses were provided on a scale of 1 to 5. The data were subsequently interpreted through a ranking of the obtained points and calculation of the standard deviation. The study sought to ascertain the efficacy of disparate methodologies for the analysis of legal support for state policy in educationThe results of the multifaceted analysis of the main concepts of state policy indicate that modern theories focus on various fundamental approaches to analysing the legal support of state policy in education. These include the institutional approach, the normative approach, the sociolegal approach, the systemic approach and the procedural approach. These approaches are tools for making managerial decisions and form the basis of a value-dependent process that includes interaction between various political actors and civil society.

Fair and Transparent Student Admission Prediction Using Machine Learning Models

Student admission prediction is a crucial aspect of academic planning, offering insights into enrollment trends, resource allocation, and institutional growth. However, traditional methods often lack the ability to address fairness and transparency, leading to potential biases and inequities in the decision-making process. This paper explores the development and evaluation of machine learning models designed to predict student admissions while prioritizing fairness and interpretability. We employ a diverse set of algorithms, including Logistic Regression, Decision Trees, and ensemble methods, to forecast admission outcomes based on academic, demographic, and extracurricular features. Experimental results on real-world datasets highlight the effectiveness of the proposed models in achieving competitive predictive performance while adhering to fairness metrics such as demographic parity and equalized odds. Our findings demonstrate that machine learning can not only enhance the accuracy of admission predictions but also support equitable access to education by promoting transparency and accountability in automated systems.

University Management System

University Management System (UMS) is designed to automate the everyday operations of administrative, academic functions in higher degree education institutions. UMS are using integrated features like online registration for students, administration file maintenance of colleges faculty details course scheduling fee transactions academic performance monitoring in simple manner. We have seen an incredible change in thesesystems over the years, largely due to increased demands for digital transformation from schools. Today, there are cloud-based access to modern UMS solutions in place which allows institutions manage their data efficiently while retaining it on secure physical storage. These systems also come with mobile capabilities that are very useful in allowing students and faculty to remain up-to-date on the latest information. Advanced data analytics has become a critical ingredient as well, enabling administrators to balance the scales through academic planning, resource allocation and performance measurement. Education institutions are increasingly using digital ways of working and UMS have enabled these organizations to streamline processes, strengthen communication channels thus making the educational journey better for all stakeholders. Keywords— University Management System (UMS), higher education, administrative automation, academic processes, cloud-based access, mobile-friendly interface, data analytics, student registration.

An Eye on the Future: Student Plans for Higher Education in Qatar

Education is identified as very critical to the achievement of the goals that were specified as strategic to Qatar’s socio-economic progress and development. At the core of the country’s policy plans is the need to develop human capacity as is highlighted in the Qatar National Vision (QNV) 2030. Not surprisingly, education has been identified as a strategic key to achieving the goals outlined in the QNV 2030. The present exploratory study employed a quantitative research design in order to investigate the factors that are likely to influence the educational aspirations of Qatari students. Drawing on Social Cognitive Theory (SCT) and Attribution Theory (AT), this study sought to examine students’ aspirations for post-secondary education in Qatar. Data for this study were collected using the Qatar Education Study (QES) survey, which is a nationally representative survey involving K-12 students in the State of Qatar. The analysis of this study’s data revealed that personal and household characteristics play an important role in shaping post-secondary educational aspirations of student participants, including age, nationality, education and employment status, as well as parental influence. Based on the study’s results, statistically significant associations were observed between personal and household variables and students’ aspirations for higher education. This study concludes with relevant recommendations and proposes future studies to explore the potential impact of individual aptitude and contextual factors on student future academic plans.

Cognitive Complexity and Degree Planning: Student Perceptions of and Needs From Technology Tools

Colleges around the country have adopted technology tools to simplify planning and registration processes and provide interventions to support students’ timely completion. However, there is little evidence of these tools’ efficacy in improving student progression and completion (c.f., Rossman et al., 2021; Velasco et al., 2020). The minimal impact of advising and planning technologies on student success is amplified among institutions supporting the students who make up the new majority of postsecondary learners—those who are Black, Latine, Indigenous, and/or low-income (BLI/LI). One possible reason for this is that such tools were not designed with the needs of this population in mind. Using process map and focus group data from students at two broad-access universities, coupled with interview data from institutional stakeholders, this study interrogates the ways that BLI/LI students engage in academic planning. We find that this process is more cognitively complex and nuanced than is typically acknowledged; program planning tools do not include the information BLI/LI students require; and low-income college students are particularly disadvantaged by these tools. As such, we find support for the hypothesis that current tools’ efficacy is muted because they do not center the needs of BLI/LI students in their design.

A Probability-Based Model for Course Completion Prediction in Online Asynchronous Learning

The sheer scale of Massive Open Online Courses (MOOCs), presents a significant challenge in delivering personalized learning experiences and effective student support. With vast participation numbers, it becomes difficult for instructors to track individual progress, pinpoint specific areas where students struggle, and understand the underlying reasons for failure to complete the course. This lack of individualized attention can lead to disengagement and higher dropout rates. A probability-based analysis offers a solution by generating student-specific predictions about their likelihood of completion. This empowers educators to proactively identify those at risk, tailor interventions, optimize resource allocation, and potentially improve the overall learning experience within the MOOC environment. This study focuses on developing a robust predictive framework to accurately estimate the probability of students completing an introductory programming course offered on the Open Learning Platform of the University of Moratuwa, Sri Lanka. The approach began with a classification model to determine the likelihood of course completion. Building upon this, a regression model was developed to generate a specific probability percentage representing the chance of a student successfully completing the course within a designated time frame. Initial findings suggested that predictions from the classification model achieved the highest accuracy when students have completed approximately 42.8% of the course materials. It is anticipated that further refinements to the methodology will improve the reliability of the predictions. A crucial aspect of this research involves determining the optimal percentage of course progress needed to yield reliable probability predictions. This is investigated through systematic analysis and experimentations including incremental model testing. The dataset encompasses diverse demographic and educational variables, enabling the identification of influential factors affecting course completion. This study provides insights on developing personalized learning strategies, intervention tactics and academic planning within online asynchronous education.

Optimal Academic Plan Derived from Articulation Agreements: A Preliminary Experiment on Human-Generated and (Hypothetical) Algorithm-Generated Academic Plans

ABSTRACT Our preliminary experiment examined a potential pain point with ASSIST, California’s database of articulation agreements. That pain point is cross-referencing multiple articulation agreements to manually develop an optimal academic plan. Optimal is defined as the minimal set of community college courses that satisfy all transfer requirements for the multiple universities a student is preparing to apply to. Accordingly, we designed a low-fidelity prototype that lists the minimal set of courses a hypothetical optimization algorithm would output based on selected articulation agreements. Twenty-four students were tasked with creating an optimal academic plan using either ASSIST (which requires manual optimization) or the optimization prototype (which already provides the minimal set of classes). Prototype users had less optimality mistakes, were faster, and provided higher usability ratings compared to ASSIST users. Going forward, future research needs to move beyond our proof of value of a hypothetical optimization algorithm and toward actually implementing an algorithm.

Optimizing faculty resource allocation in higher education: A mathematical model for strategic planning

This paper introduces a new mathematical model aimed at improving how faculty resources are allocated in higher education institutions. The model takes into account the complexities of student enrollment, teaching quality, and program offerings. It provides a structured method to estimate faculty needs, including both Ph.D. holders teaching core courses and teaching assistants or lecturers managing practical courses, labs, and related tasks. By considering factors such as class sizes, faculty workloads, and student enrollment patterns, the model offers useful insights for academic planning. Two case studies from Hafr Al Batin University illustrate the model's practical value and flexibility. These examples show how the model can support informed decision-making, helping to maintain a balance between student numbers and teaching quality. The paper concludes by highlighting the importance of data-driven planning in the changing field of higher education, suggesting future research directions, and positioning the model as a key tool for improving the management and administration of higher education. The main goal is to ensure a high-quality education for students while making efficient use of resources.

Bibliometric Analysis on Precision Agriculture Technology

This study employs a bibliometric analysis using VOSviewer to visualize the authorship network within the domain of precision agriculture, identifying key researchers and their collaborative relationships. By mapping the connections based on publications from a specified time period, the analysis highlights the central figures like Erickson, B, who play pivotal roles in the network and reveals the interlinkages among various contributors. The study provides insights into the structural dynamics of research collaborations and elucidates the influence patterns among the scholars. Despite the inherent limitations such as database selection bias and the static nature of the bibliometric snapshot, the results offer valuable implications for enhancing research collaboration, academic planning, and strategic positioning within the scholarly community. This approach not only aids in recognizing influential entities and emerging talents but also assists institutions and funders in making informed decisions that could drive impactful research in precision agriculture.

Striving for Quality Higher Education: The Quandaries of Academic Planning and Quality Assurance Directorate at the University for Development Studies

The study examined the quandaries of the Directorate of Academic Planning and Quality Assurance (DAPQA) of the University for Development Studies. The study adopted a mixed research approach using purposive sampling to select two staff members from the Directorate and fourteen DAPQA representatives from all the various schools and faculties in the university. The researchers personally administered the questionnaires and conducted the interviews. Descriptive statistics and frequencies were employed to analyze the quantitative data, while the qualitative data were transcribed and coded for easy identification. The study revealed that the directorate is faced with poor cooperation from the university's academic and non-academic staff. It also came to light that there were inadequate personnel and limited office space and funds to carry out their activities. The study, therefore, recommends recruiting qualified staff and continuing workshops for existing staff of the university to appreciate the role of DAPQA and the need to avail themselves whenever needed. Again, university management should organize in-service training for the staff of DAPQA and provide enough office space and funds to carry out its activities.

Lived Experiences of Neurodiverse Students: A Review

This study aims to examine available literature on neurodiversity, particularly as it relates to neurodiverse students’ lived experiences. This study utilized the scoping review method to effectively map how research about neurodiverse students has been designed and conducted. Through a thorough search of four databases, articles were selected for data extraction and review based on the named criteria. Among all the studies reviewed, one of the themes that stood out was the view that only a few research directly assessed the needs of students with neurodiversity. It is also worth noting that of all kinds of neurological conditions, Autism Spectrum Disorder and Asperger Syndrome received due attention among all the papers about neurodiversity. Autism Spectrum Disorder (ASD) and high-functioning autism received greater attention, followed by Asperger syndrome. Research efforts concerning the lived experiences of neurodiverse students are limited, particularly in Africa, where this research found no article that captured the lived experiences of neurodiverse students from their perspectives. These findings build on existing research by ascertaining whether neurodiverse students’ voices are acknowledged enough by researchers who could influence inclusion in academic planning, curriculum design, social activities and general academic life. Findings from this research imply that it would be of utmost assistance to researchers if gaps in neurodiversity research are identified to inform ideas for future research. Future studies ought to focus on African countries to explore the situation and academic life of neurodiverse students and not merely depend on the input of teachers, parents and neurodiversity professionals.

Showing authentic examples of academic and career trajectories to influence college students' career exploration

College students increasingly use digital information resources to help them make academic and career decisions, but the effects of digital information tools on students' career exploration outcomes are not well understood. We investigate the impact of an online tool that shows the full sequence of course enrollments and the first career destination of recent graduates with matched interests. We conducted a randomized controlled experiment with 234 undergraduate students at a U.S. university to examine the tool's impact on students' career exploration outcomes, specifically their self-efficacy in academic planning for career exploration and behavioral intentions for career exploration. We did not find clear evidence that the tool increased students' self-efficacy and behavioral intentions. However, our exploratory analysis shows that the tool benefited students who were at a later stage in their career decision-making process. We also found that students' awareness of official information sources from archival student records and awareness of holistic information that combines academic and career decisions are important predictors of self-efficacy and behavioral intentions. This study presents a nuanced view of the potential of digital tools to enhance career exploration outcomes through information support. It has important implications for institutional administrators to integrate existing digital resources with traditional career services, creating a more comprehensive support system for students.

ENGINEERING-GEODETIC SURVEYING. GEOMETRIC LEVELING OF THE ROUTE

The purpose of leveling the route is to determine the elevations of all the control points, including the beginning, middle, and end of curves, plus points, and points on transverse profiles. Longitudinal and transverse leveling is carried out after the route has been set out. The results of leveling (elevation measurements) are subsequently used for constructing the longitudinal profile of the route and the transverse profiles.The paper outlines the main principles and methods of leveling, taking leveling readings on rods, referencing the road route to benchmarks, leveling junction and intermediate points, balancing elevation differences, and calculating junction and intermediate points. The paper also describes the control of route leveling and plotting the projected line on the longitudinal profile.Engineering-geodetic surveying, specifically geometric leveling of the route, is an important component of educational geodetic practice. Geodetic practice for students is conducted according to the academic curriculum and serves as a continuation of the learning process in the field. It completes the theoretical course and is conducted according to the academic plan. During practical training, students acquire skills in working with geodetic instruments and processing the results of field measurements, becoming familiar with the main types of engineering-geodetic work during surveys and construction of engineering structures. Students are required to participate in all types of work, conduct the necessary measurements, and process them in the office. Practical training in geodetic practices provides students with hands-on experience in applying theoretical knowledge to real-world scenarios. Through fieldwork, students gain proficiency in using a variety of geodetic instruments such as levels, total stations, and GPS receivers. They learn how to set up and operate these instruments accurately to collect precise measurements of elevation and distance. Furthermore, students learn the importance of teamwork and collaboration during field surveys. Working together with peers, they divide tasks, communicate effectively, and problem-solve on-site challenges that may arise. These collaborative experiences not only enhance their technical skills but also cultivate essential soft skills such as leadership, communication, and adaptability.

APPLICATION OF RANDOM FOREST METHOD TO PREDICTION OF STUDENT CANDIDATES ACCEPTED IN THE SNMPTN PATHWAY (CASE STUDY AT UNIVERSITAS LAMBUNG MANGKURAT)

Academic planning is an essential aspect that needs to be carried out to plan the teaching and learning process in a campus, such as the admission of new students through the SNMPTN. At Lambung Mangkurat University, it is known that the partici- pants who took the SNMPTN during the 2021 admission period amounted to 7,703. It is recognized that selecting candidates is not easy due to many prospective students passing the selection but choosing to withdraw. Therefore, a system is needed to predict the graduation of prospective students through the SNMPTN. This research utilizes the Random Forest method to predict the graduation of prospective students through the SNMPTN. The data will be divided into 90% for training data and 10% for testing data, then using classification parameters with 300 n-estimators. The research yielded a precision value of 0.72, recall value of 0.46, and system accuracy of 89.3% For further research recommendations, other prediction methods can be explored to forecast the graduation rate of students through the SNMPTN, or a comparison of methods can be con- ducted to determine which method is more effective.

Optimizing Undergraduate Curriculum Based on Students' Career Planning and Curriculum Experience: A Case Study of Undergraduate Accounting Major at a University

Undergraduate accounting students-often lack a strong sense of identification with their major, even with the program under the conditions of meeting national standards for teaching quality in accounting. The current state of research conducted at the macro level of the curriculum in the accounting undergraduate program does not adequately explain the resistance of undergraduate accounting students in their progress of studies. The purpose of this study is to approach undergraduate accounting students in a university utilizing questionnaires and interviews, and to explore the shortcomings and deficiencies in the undergraduate accounting curriculum in universities, specifically at the level of student experience. The article gives the conclusion that colleges and universities should promote the construction of professional literacy, the enhancement of professional identity, and the development of future planning ability of undergraduate accounting students from the aspects of optimizing the deficiencies in the curriculum in teaching and providing assistance for students' employment and further pursuit in academic planning.

STUDENT SUCCESS COACHING IN HIGHER EDUCATION: A REVIEW OF LITERATURE

Student success coaching has emerged as a vital support mechanism in higher education. It aims to bolster academic performance, personal development, and overall well-being. This paper reviews the literature on student success coaching and synthesizes existing research to illuminate its evolving landscape. The review delves into the nature of student success coaching, characterized by personalized guidance, frequent interactions, and a focus on individual students’ needs. Definitions and models of student success coaching are explored, addressing students’ diverse aspirations and challenges. Trends in student success coaching underscore its effectiveness in integrating students into academic and social aspects of postsecondary institutions, thereby breaking down barriers to success. Coaching interventions encompass goal setting, academic planning, and connection to resources, all geared toward facilitating student achievement. This paper identifies areas for further research, emphasizing the need to explore the effectiveness of coaching across diverse student populations and its long-term impact beyond immediate academic outcomes. Additionally, institutional factors and the role of technology in enhancing coaching programs are proposed as avenues for future inquiry.

Artificial Intelligence: Its Role and Potential in Education

Artificial intelligence (AI), which has attracted great attention in recent years, has been widely used in the field of education as in many other fields. AI in education is used to improve student learning, support teachers and provide a more personalized educational experience. AI plays an important role with adaptive learning systems in improving students' learning processes. These systems assess students' individual needs and provide them with appropriate learning materials. AI also monitors students' performance, identifies their weaknesses, and provides additional support in these areas. Thus, students are enabled to learn more effectively and to reveal their full potential. By supporting teachers, AI facilitates classroom management and helps teachers use their time more efficiently. Automated assessment systems allow teachers to quickly assess assignments and exams, while improving the process of providing feedback. In addition, AI also helps teachers understand students' interests and learning styles, so that more personalized instruction can be offered. Another important use of AI in education is student counseling. AI-based counseling systems can guide students in matters such as career choices, university applications, and academic planning. These systems can provide students with viable career options, support the application process, and help them identify their future goals. As a result, the use of AI in education has great potential to improve student learning processes, provide support to teachers and provide a more personalized educational experience. In this study; The subject of AI was examined in a general framework under the title of education and the role of AI in education was discussed. It is thought that AI will contribute to the field by revealing the teacher and how it can be used in the field of education.

“Failure-to-warn” when giving advice to students? No evidence for an ethnic bias among teacher students in Germany

Receiving appropriate, unbiased advice from their teachers is important for students’ smaller- and larger-scale educational decisions. However, teachers’ concerns about being or appearing to be prejudiced may interfere and lead them to provide encouraging advice to students belonging to negatively stereotyped groups even when it is not warranted (failure-to-warn phenomenon). In this experimental study, we aimed to replicate findings from the US and tested whether teacher students in Germany provided overly encouraging advice regarding the academic plans of a student with a Turkish (vs. German) name. Teacher students (n = 174) saw the overly ambitious timetable of a (supposed) student with a Turkish or German name and gave advice online on rating scales and in an open-response format. In their advice, they indicated, among others, the perceived demands of the timetable, possible affective and social consequences for the student, and the need to reconsider the timetable. Contrary to expectations and findings from the US, our analyses did not indicate differences in the advice that students with Turkish vs. German names received. Instead, teacher students warned students with a Turkish and German name equally of the difficulties associated with their potential timetable. We discuss both methodology- and theory-related potential explanations for these unexpected findings.

[Translated article] Compounding training programme for pharmacy technicians using a digital platform and simulation techniques

ObjectiveTo describe a compounding training plan in a tertiary hospital pharmacy service. The project aimed pharmacy assistant technicians to use a digital training platform and simulation techniques. MethodsTwo training programs were designed, one for sterile and the other for non-sterile drugs. Each programme consists of several phases: a basic online training course (digital e-learning platform), a practical simulation workshop, a supervised practice in real conditions, and a final verification by the pharmacist to qualify the technician. Both programs include continuous and accredited evaluation by the hospital's Continued Education Commission.A satisfaction survey on training (e-lerning platform) was designed and conducted for pharmacy technicians (sterile and non-sterile). ResultsThe project has been running for 3 years. Six specialist pharmacists from different areas involved in compounding are responsible for training and continuous evaluation. Twenty-one technicians have been trained, and nineteen have obtained qualifications. Two of them were found to be unfit. Currently, we employ13 pharmacy technicians who were initially trained.The participation rate in the satisfaction survey on training (e-learning platform) was 61.5% (n=8) out of a total number of current developers (n=13). Overall, 62.5% of technicians reported being satisfied or very satisfied, while the remaining 37.5% were indifferent. ConclusionsCompounding training program is currently in its third year. It has been crucial in delegating tasks to pharmacy technicians. The use of digital technology is essential in this training. We consider that, specific training in compounding, is indispensable and should be included in the academic plan for pharmacy technicians.