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Paulina Berríos; Estefanía Álvarez; Karen Gutiérrez; Antonia Santos – Association for Institutional Research, 2024
This article delves into the challenges of institutional data collection processes in higher education, particularly regarding diversity reporting. The study this article is based on focuses on enhancing inclusivity by introducing a nonbinary sex category into the institutional data of a distinguished Chilean public university. In the Chilean…
Descriptors: Gender Identity, LGBTQ People, Classification, Data Collection
Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
Jasinski, Lisa; Nokkala, Terhi; Juusola, Henna – European Journal of Higher Education, 2021
When conceived of as both a research strategy and mode to present findings, vignettes can be combined with various qualitative methodologies in higher education research. Rather than being a discipline unto itself, higher education research is best understood as a multi and cross-disciplinary field of study that, we contend, is made richer by its…
Descriptors: Vignettes, Educational Research, Educational Benefits, Research Methodology
Wonkyung Choi; Jun Jo; Geraldine Torrisi-Steele – International Journal of Adult Education and Technology, 2024
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…
Descriptors: College Students, Data Analysis, Data Collection, Learning Analytics
So, Joseph Chi-ho; Wong, Adam Ka-lok; Tsang, Kia Ho-yin; Chan, Ada Pui-ling; Wong, Simon Chi-wang; Chan, Henry C. B. – Journal of Technology and Science Education, 2023
The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students' particulars such as their academic background, current study and student activity records, their attended higher education institution's expectations of graduate attributes and self-assessment of their own generic…
Descriptors: Pattern Recognition, Artificial Intelligence, Higher Education, College Students
Jaiswal, Garima; Sharma, Arun; Yadav, Sumit Kumar – International Journal of Information and Communication Technology Education, 2019
In the world of technology, tools and gadgets, a huge amount of data is produced every second in applications ranging from medical science, education, business, agriculture, economics, retail and telecom. Higher education institutes play an important role in the overall development of any nation. For the successful operation of these institutions,…
Descriptors: Prediction, Dropouts, Dropout Rate, Classification
Motz, Benjamin; Busey, Thomas; Rickert, Martin; Landy, David – International Educational Data Mining Society, 2018
Analyses of student data in post-secondary education should be sensitive to the fact that there are many different topics of study. These different areas will interest different kinds of students, and entail different experiences and learning activities. However, it can be challenging to identify the distinct academic themes that students might…
Descriptors: Data Collection, Data Analysis, Enrollment, Higher Education
Sipes, Shannon M. – Interdisciplinary Journal of Problem-based Learning, 2017
Few of the papers published in journals and conference proceedings on problem-based learning (PBL) are empirical studies, and most of these use self-report as the measure of PBL (Beddoes, Jesiek, & Borrego, 2010). The current study provides a theoretically derived matrix for coding and classifying PBL that was objectively applied to official…
Descriptors: Data Collection, Problem Based Learning, Program Development, Test Construction
Siekmann, Gitta; Korbel, Patrick – National Centre for Vocational Education Research (NCVER), 2016
This report explores the definition and selection of science and technology-related (STEM) jobs in-depth. Examples from the United States, United Kingdom, and Australia are described, with similarities and differences highlighted. [This document was produced by the author(s) based on their research for "What Is STEM? The Need for Unpacking…
Descriptors: STEM Education, Technical Education, Vocational Education, Job Skills
Noel, Jana; Earwicker, David P. – Journal of Higher Education Outreach and Engagement, 2015
This study was performed to document the strategies and methods used by successful applicants for the 2010 Carnegie Community Engagement Classification and to document the cultural shifts connected with the application process and receipt of the Classification. Four major findings emerged: (1) Applicants benefited from a team approach; (2)…
Descriptors: Community Involvement, School Community Relationship, Higher Education, Classification
Bendjebar, Safia; Lafifi, Yacine; Seridi, Hamid – International Journal of Web-Based Learning and Teaching Technologies, 2016
In e-learning systems, the tutors play many roles and carry out several tasks that differ from one system to another. The activity of tutoring is influenced by many factors. One factor among them is the assignment of the appropriate profile to the tutor. For this reason, the authors propose a new approach for modeling and evaluating the function…
Descriptors: Electronic Learning, Teaching Methods, Classification, Student Needs
Irby, Stefan M.; Phu, Andy L.; Borda, Emily J.; Haskell, Todd R.; Steed, Nicole; Meyer, Zachary – Chemistry Education Research and Practice, 2016
There is much agreement among chemical education researchers that expertise in chemistry depends in part on the ability to coordinate understanding of phenomena on three levels: macroscopic (observable), sub-microscopic (atoms, molecules, and ions) and symbolic (chemical equations, graphs, etc.). We hypothesize this "level-coordination…
Descriptors: Chemistry, Formative Evaluation, Graduate Students, College Students
Namdev Dhamdhere, Sangeeta – Turkish Online Journal of Distance Education, 2015
Every academic institution contributes to knowledge. The generated information and knowledge is to be compiled at a central place and disseminated among the society for further growth. It is observed that the generated knowledge in the academic institute is not stored or captured properly. It is also observed that many a times generated…
Descriptors: Foreign Countries, Knowledge Management, Higher Education, Universities
Bozkurt, Aras; Kumtepe, Evrim Genc; Kumtepe, Alper Tolga; Aydin, Irem Erdem; Bozkaya, Müjgan; Aydin, Cengiz Hakan – European Journal of Open, Distance and E-Learning, 2015
This paper presents a content analytic approach on doctoral dissertations in the field of distance education in Turkish Higher Education context from the years of 1986 through 2014. A total of 61 dissertations were examined to explore keywords, academic discipline, research areas, theoretical/conceptual frameworks, research designs, research…
Descriptors: Foreign Countries, Distance Education, Doctoral Dissertations, Higher Education
Siekmann, Gitta; Korbel, Patrick – National Centre for Vocational Education Research (NCVER), 2016
Current definitions of STEM skills are inconsistent and not specific enough to inform education and skill policies and initiatives, potentially leading to a number of unsubstantiated and uncoordinated responses. There is a danger of generating a domestic oversupply of graduates in science, mathematics, engineering and technology while ignoring the…
Descriptors: STEM Education, Technical Education, Vocational Education, Job Skills