Higher Education Database Research Articles

Initial crisis leadership during COVID-19 higher education: a systematic review

ABSTRACT The effect of the novel coronavirus pandemic (COVID-19) on the higher education sector is profound. The scholarly research on COVID-19 effects in higher education have largely focused on presenting intra-period facts, often with poor contextualisation to the broader evidence base. This manuscript draws on the first comprehensive systematic literature reviw database comprising 138 publications, the COVID-19 in Higher Education Database, to provide a first glance at six months of COVID-19 crisis leadership responses in the higher education sector. This systematic review aims to consolidate learning and teaching literature between 1 January 2020 and 30 June 2020 to share timely educational knowledge with the sector. Through a thematic analysis, the authors identified six key themes emerging in the literature: academic development, edtech, student experience, pedagogy, policy and wellbeing. They found that there were consistencies in the emerging literature across different disciplines and jurisdictions, despite the general lack of interaction between these manuscripts.

Post-independence health research productivity in Portuguese-speaking African countries: A bibliometric analysis of 43 years of research and higher education in Mozambique

BackgroundAfrica has a high double burden of infectious and non-communicable diseases underscoring the critical need for robust scientific research. However, it is also associated with low scientific research productivity. Mozambique, which gained independence in 1975, serves as a poignant example. However, there remains a notable scarcity of evidence evaluating the country's trajectory in scientific and academic development. This study aims to evaluate 43 years of health-related scientific knowledge production through bibliometric analysis, focusing on key indicators. Additionally, it seeks to characterize the higher education institutions within the country. MethodsThe data was retrieved from the Web of Science Core Collection using an advanced search tool with Boolean research strategies, covering the period from 1976 to 2022 for all PALOP and 1976 to 2019 for Mozambique. To map Mozambican higher institutions, information was sourced from the Ministry of Science Technology and Higher Education database. Descriptive statistics were employed to summarize the findings, while the VOSviewer program version 1.6.19 was utilized to visualize distance-based bibliometric networks, focusing on co-authorship among institutions and keyword co-occurrence. ResultsPortuguese-speaking African countries (PALOP) contribute 2.5 % (10,933 out of 442,309) to Africa's total scientific output, with Mozambique leading at 63.6 % (6,951 publications) followed by Angola at 16.6 % (1,811 publications). All PALOP countries experienced decreased scientific productivity during the third year of the COVID-19 pandemic. In Mozambique, over 70 % (1,710 out of 2,380) of health-related publications from 2011 to 2019 were concentrated in this period. Key journals for health sciences include PLOS ONE, Malaria Journal, and Tropical Medicine & International Health, focusing on HIV, malaria, and tuberculosis. Higher education institutions in Mozambique show regional disparities, with 67.9 % in the South and only 8.9 % in the North, indicating significant inequality in their distribution across the country. ConclusionThis study highlights Mozambique's significant progress in health research productivity over 43 years, establishing it as a leader among PALOP countries. The substantial increase in publications, particularly after 2008, underscores the nation's growing research capacity and commitment to addressing critical health challenges such as HIV, malaria, and tuberculosis. However, regional disparities in higher education access and limited research contributions from private universities remain high in Mozambique.

Minat Berwirausaha Pada Gen-Z di Era Digital

The current interest in entrepreneurship was a solution to the problem of the large number of human resources that cannot yet be fully absorbed by existing employment opportunities. This is a challenge in itself, especially for universities, to ascertain what factors can influence existing programs so that they can be strengthened. Moreover, students currently fall into the Generation Z category, which has the characteristics of being more careful and with a long-term perspective. The objectives of this research include finding out the role of entrepreneurial literacy, income expectations, and digital literacy. The population in this study are active students in Indonesia, seen in the Higher Education Data Base (PDDikti) statistical data of 6,028,003 students. Meanwhile, the sample size in this study was calculated using the Slovin Formula at an error rate of 5%, obtained at 400 students. The sampling technique used is Simple Random Sampling. The data in this research uses quantitative data sourced from primary data in the form of tabulated results from questionnaires distributed. The analytical method in this research used multiple regression analysis. The results of the calculation of variable X1 obtained tcount of 4.408 > t table and a significant value of 0.000 < 0.05, variable significant value of 0.004 <0.05. This shows that the influence of entrepreneurial literacy, income expectations, digital literacy on entrepreneurial interest.

Artificial intelligence in higher education database (AIHE V1): Introducing an open-access repository

Artificial intelligence in higher education database (AIHE V1): Introducing an open-access repository

Artificial intelligence in higher education database (AIHE V1).

Artificial intelligence in higher education database (AIHE V1).

Academic Dashboard For Monitoring KPI Based Using Data Feeder Dikti

University management requires accurate and fast academic reports that make it easier to make strategic decisions and in order to improve the quality of education. Therefore we need a tool that can monitor, evaluate and measure the performance of universities. A common problem is that there is a lot of academic data stored but to present it in reports at the time of evaluating academic activities is difficult and takes a long time. Academic evaluation can be presented with a dashboard so that it becomes easy for decision making. Dashboard is a page that shows graphs as KPIs (Key Performance Indicators) of an organization and provides all the important measurements needed to make key executive decision making. Universities in Indonesia report data on students, lecturers and lecture activities to the PDDIKTI (Higher Education Database). The data contained in the PDDIKTI Feeder is made an academic Dashboard in the form of visualization to assist and support decision making at the academic level and also to monitor using KPI as an evaluation. With the existence of an academic dashboard based on KPI, the presentation of reports becomes faster and easier to understand because it is in the form of visuals and indicators to find out what things need to be improved and the extent to which the achievements of each academic component are used as benchmarks in submitting study program accreditation.

DUE TO THE LEGAL UNDERSTANDING OF PRIVATE Universities IN THE SHADOW OF DIFFERENT FOUNDATIONS (STUDY OF UNIVERSATION OF HEALTHY SOLAR AKBID INTO DR SOETOMO UNIVERSITY SURABAYA)

The large number of private universities in Indonesia creates a quality gap. The unification of private universities is a solution to improve the quality of private higher education. One of the successful ones is the Surya Sehat Midwifery Academy Surabaya with Dr Soetomo University Surabaya. However, the unification process still needs to be examined more deeply about the basic considerations for the unification between the two private universities and the legal consequences of the unification. The unification of the Surya Sehat Midwifery Academy with Dr Soetomo University resulted in the loss of the Surya Sehat Midwifery Academy in the higher education database and merged into Dr Soetomo University into a midwifery study program at the health sciences faculty. which is quite long, namely three years, causing legal uncertainty in the field. This should not need to happen if the government, in this case the Ministry of Education and Culture, applies a Standard Operating Procedure (SOP) for licensing and furthermore to avoid service barriers for alumni of the Surya Sehat Midwifery Academy Surabaya, it is necessary to include alumni data in the health sciences faculty database so that it is physically integrated. as well as virtually.

Evaluation Model of Internal Quality Assurance System in Universities

This study aims to determine: 1) implementation of internal quality management evaluation, 2) development of an evaluation model, 3) testing a new model of internal quality evaluation in the quality cycle, and 4) the effectiveness of the implementation of the internal quality management evaluation model that has been implemented at the university. Methods This research uses a qualitative approach with types. Data collection techniques are carried out through in-depth interviews, participant observation, photography and documentation. The data were analyzed using the model of Miles and Huberman's interactive transformation consisting of data collection, data reduction, data display and conclusion. The validity of the data is done by testing the credibility, transferability, dependability, and confirmability. This study found that first, the internal quality management evaluation model used by three universities was PPEPP (Determination, Implementation, Evaluation, Control, Improvement). Second, creating an evaluation model based on AIS (Academic Information System) and the Higher Education Database (PD Dikti). And third, testing a new model of internal quality evaluation in the quality cycle, namely monitoring and evaluation, recording and inspection, and action.

Prediction of Undergraduate Student’s Study Completion Status Using MissForest Imputation in Random Forest and XGBoost Models

The number of higher education graduates in Indonesia is calculated based on their completion status. However, many undergraduate students have reached the maximum length of study, but their completion status is unknown. This condition becomes a problem in calculating the actual number of graduates as it is used as an indicator of higher education evaluation and other policy references. Therefore, the unknown completion status of the students who have reached the maximum length of study must be predicted. The research compared the performance of Random Forest and Extreme Gradient Boosting (XGBoost) classification models in predicting the unknown completion status. The research used a dataset containing 13.377 undergraduate students’ profiles from the Higher Education Database (PDDikti), Ministry of Education, Culture, Research, and Technology. The dataset was incomplete, and the proportion of missing data was 20,9% of the total data. Because missing data might lead to prediction bias, the research also used MissForest imputation to overcome the missing data in the classification modelling and compared it to Mean/Mode and Median/Mode imputation. The results show that MissForest outperforms the other two imputations in both classifiers but requires the longest computation time. Furthermore, the XGBoost model with MissForest is significantly superior to the Random Forest model with MissForest. Hence, the best model chosen to predict the completion status is XGBoost with MissForest imputation.

Data Quality Assessment on Lecturer Primary Data: A Case Study on Higher Education Database at Ministry of Education and Culture Republic of Indonesia

The quality of an organization’s data is an important component that can influence various policies taken in technical and strategic terms. This study aims to analyze the quality of basic data for lecturers on resource information systems whose data is integrated with the Higher Education Database (PDDikti). Measurement of data quality based on the rules that have been set in the main unit of higher education data management which is then determined in this study includes 4 dimensions of data quality, namely completeness, validity, accuracy, and currency. The application of quantitative methods by processing data and then analyzing the quality of the data using qualitative methods based on the dimensions that have been determined for the basic data quality assessment for lecturer in every tertiary institution in Indonesia. The results showed that the quality of the data had been resolved by 91.94% so that it can be used as a basis for decision making according to predetermined standards. The results of this data quality research can be used as supporting information in policy making in terms of developing and improving data quality in the scope of higher education, especially those related to the quality of basic data for lecturers.

Literature Study of Problem Based Learning Model Against Students Mathematical Motivation (Based on Indonesian Language Book)

This study aims to describe whether the Problem Based Learning Model can be used for students' motivation problems in learning mathematics, what kind of motivation is successfully provided by the Problem Based Learning Model, and how the Problem Based Learning Model can make students have motivation in learning mathematics. The research method used is the Literature Research Method, by conducting a literature review through books in Indonesian. To maintain the quality of the material being studied, Indonesian language books are often used as references and written by experts (for example professors) which are proven based on tracking activities carried out in various journals, books, and from the Higher Education Database (pddikti). Data analysis techniques were carried out in 3 stages, namely: organize, synthesize, and identify. The results showed that the Problem Based Learning Model can be used for students' motivation problems in learning mathematics, intrinsic motivation is the type of motivation provided by the Problem Based Learning Model and the Problem Based Learning Model can make students have motivation in learning Mathematics because it is directly associated with the real world, so students feel mathematics is very useful and motivation will emerge.

Evaluation of university accreditation prediction system

Higher education accreditation body (Badan Akreditasi Nasional Perguruan Tinggi/BAN-PT in Indonesian) is an Indonesian body with the main task to assess the quality of Indonesian university. The assessment result is called accreditation, which has 5 years of validation time. In order to monitor the quality, University has an internal mechanism which is called an internal quality assurance system (Sistem Penjaminan Mutu Internal/SPMI in Indonesian). Usually, SPMI assesses the quality periodically, one or two times each year. This process needs much effort, i.e. time, manpower, and financial cost. Sometimes, internal auditor of the university does not have sufficient knowledge, as much as BAN-PT assessor. This condition causes a lack of assessment accuracy, then causes the quality of SPMI itself. On the other hand, University has abundant of condition data, saved in higher education database (HEDB). This paper proposes to exploit the availability of data in this case. Therefore university able to monitor the quality by machine learning process periodically without much effort as manual SPMI process. Furthermore, this paper evaluates two machine learning methods, i.e. naive Bayes and K-Nearest Neighbor (K-NN). This proposal exploits several data: student, academic, admission, and alumna. K-NN and naive Bayes work in registrant and capacity ratio, student registration ratio, average student Grade Point Average (GPA) in late five years, and on-time graduation scale. The experiment results show the average accuracy of naive Bayes and KNN are 70% and 95.2% respectively.

A preliminary study of multiple college admission criteria in Taiwan: the relationship among motivation, standardized tests, high school achievements, and college success

ABSTRACTA new college admission policy will be implemented in Taiwan in 2022. The purpose of this study was to understand the relationship between admission criteria and college success. Data was obtained from the Taiwan Higher Education Database; a sample size of 8443 students from 156 universities was used in this study. By using the structural equation model, this study tested a research model that included factors such as motivation, standardized test scores, high school achievements, and college success. The findings revealed that the General Scholastic Ability Test scores (in Chinese, English, Social Studies) and high school average academic grades are significantly associated with college success. A student’s motivation to complete a certain major can significantly predict the quality of student effort and influence college success. These findings highlight the importance of some admission criteria and provide practical implications for educational policy-makers, school administrators, students, and parents.

Viscous Open Data: The Roles of Intermediaries in an Open Data Ecosystem

Open data have the potential to improve the governance of universities as public institutions. In addition, open data are likely to increase the quality, efficacy and efficiency of the research and analysis of higher education systems by providing a shared empirical base for critical interrogation and reinterpretation. Drawing on research conducted by the Emerging Impacts of Open Data in Developing Countries project, and using an ecosystems approach, this research paper considers the supply, demand and use of open data as well as the roles of intermediaries in the governance of South African public higher education. It shows that government's higher education database is a closed and isolated data source in the data ecosystem; and that the open data that are made available by government is inaccessible and rarely used. In contrast, government data made available by data intermediaries in the ecosystem are being used by key stakeholders. Intermediaries are found to play several important roles in the ecosystem: (i) they increase the accessibility and utility of data; (ii) they may assume the role of a “keystone species” in a data ecosystem; and (iii) they have the potential to democratize the impacts and use of open data. The article concludes that despite poor data provision by government, the public university governance open data ecosystem has evolved because intermediaries in the ecosystem have reduced the viscosity of government data. Further increasing the fluidity of government open data will improve access and ensure the sustainability of open data supply in the ecosystem.

The Effect of Student Financial Constraints on University Non-Completion Rates

<p>The year 2009 saw the government of Zimbabwe redesigning cost-sharing in higher education to lean more towards higher contributions by students and private players. This study was aimed at investigating the effects that this strategy has on university completion rates by students from low socio-economic backgrounds. The study used a quantitative design methodology in a longitudinal study framework incorporating data from three cohorts embarking on four-year study programmes from 2009 to 2014. Administrative data from the Zimbabwe Council for Higher Education database involving six state universities was used. The findings reveal that the graduation rates decreased from 86% in the 2009 cohort to 76% in the 2010 cohort and 75% in the 2011 cohort. This finding coincides with the period from 2013 onwards when cadetship funds dried off. Thus the study clearly revealed a problem of increasing attrition rates creeping into the revered and quality-assured Zimbabwean higher education system. The study recommends the need for conceited efforts by the private sector, government and universities in funding higher education through loans and other forms of sponsorship.</p>