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Gale Macleod; Marshall Dozier; Rosa Marvell; Gerri Matthews-Smith; Malcolm R. Macleod; Jing Liao – Oxford Review of Education, 2024
This research aimed to describe and evaluate research on the Postgraduate Taught (PGT) sector in the UK from January 2008 to October 2019. The focus on PGT allowed a detailed analysis of an often overlooked part of the HE sector. Methodologically, the research is original in its use of an innovative machine learning approach to a systematic…
Descriptors: Research, Artificial Intelligence, Masters Programs, Foreign Countries
Kumar, Chandan Jyoti; Das, Priti Rekha – International Journal of Developmental Disabilities, 2022
Autism Spectrum Disorder (ASD) is a highly heterogeneous set of neurodevelopmental disorders with the global prevalence estimates of 2.20%, according to DSM5 criteria. With the advancements of technology and availability of huge amount of data, assistive tools for diagnosis of ASD are being developed using machine learning techniques. The present…
Descriptors: Autism Spectrum Disorders, Clinical Diagnosis, Artificial Intelligence, Observation
Rybinski, Krzysztof – Higher Education Research and Development, 2022
This article develops a machine learning methodology to analyse the relationship between university accreditation and student experience. It is applied to 98 university accreditations conducted by the Quality Assurance Agency (QAA) in the UK in 2012-2018, and 263,025 university ratings in three categories posted by students on the website…
Descriptors: Program Evaluation, Accreditation (Institutions), Student Experience, College Students
Wyness, Gill; Macmillan, Lindsey; Anders, Jake; Dilnot, Catherine – Education Economics, 2023
Students in the UK apply to university with teacher-predicted examination grades, rather than actual results. These predictions have been shown to be inaccurate, and to favour certain groups, leading to concerns about teacher bias. We ask whether it is possible to improve on the accuracy of teachers' predictions by predicting pupil achievement…
Descriptors: Foreign Countries, Prediction, Grades (Scholastic), Expectation
Schmucker, Robin; Wang, Jingbo; Hu, Shijia; Mitchell, Tom M. – Journal of Educational Data Mining, 2022
We consider the problem of assessing the changing performance levels of individual students as they go through online courses. This student performance modeling problem is a critical step for building adaptive online teaching systems. Specifically, we conduct a study of how to utilize various types and large amounts of log data from earlier…
Descriptors: Academic Achievement, Electronic Learning, Artificial Intelligence, Predictor Variables
Tyrer, Freya; Kiani, Reza; Rutherford, Mark J. – Journal of Intellectual & Developmental Disability, 2021
Background: There is a need to systematically compare and contrast mortality predictors and disparities in people with intellectual disabilities (ID) for global prevention strategy development. Method: Bibliographic databases and grey literature were searched using systematic review methodology and the machine learning tool "Abstrackr."…
Descriptors: Intellectual Disability, Death, Predictor Variables, Prevention
Galloway, Rory – Primary Science, 2020
Technology in farming has advanced a great deal, but still has a long way to go. At the beginning of 2019, the then Environment Secretary, Michael Gove, stated that the United Kingdom is on the verge of a fourth agricultural revolution. This fourth revolution is being called the technological revolution, with developments involving artificial…
Descriptors: Foreign Countries, Agricultural Occupations, Agricultural Engineering, Agricultural Production
Tarling, Georgie; Melro, Ana; Kleine Staarman, Judith; Fujita, Taro – Pedagogies: An International Journal, 2023
Coding bootcamps targeting diverse learners are increasingly popular. However, little research has focused on the student experience of these courses: what pedagogic practices make learning coding meaningful for them and why. In a previous paper, we proposed a conceptual framework outlining three dimensions of learning opportunities in relation to…
Descriptors: Student Attitudes, Coding, Programming, Computer Science Education
A. Mark Langan; W. Edwin Harris – Higher Education: The International Journal of Higher Education Research, 2024
This study explores dissatisfaction and neutrality metrics from 12 years of a national-level undergraduate student survey. The notion of dissatisfaction is much less prevalent in the narratives surrounding student survey outcomes, and the underpinning metrics are seldom considered. This is despite an increasingly vociferous debate about…
Descriptors: Undergraduate Students, Student Satisfaction, Student Attitudes, Foreign Countries
Luengo, Óscar; García-Marín, Javier; de-Blasio, Emiliana – Comunicar: Media Education Research Journal, 2021
Social media has significantly transformed how political discussions and deliberations occur, mainly by providing a digital realm for the public sphere. This study aims to analyse the extent of polarised opinions across Spain, Italy and the United Kingdom regarding COVID-19 during 2020 within social media. To do this, we examined YouTube comments…
Descriptors: COVID-19, Pandemics, Social Media, Foreign Countries
Langan, A. M.; Harris, W. E.; Barrett, N.; Hamshire, C.; Wibberley, C. – Studies in Higher Education, 2018
There is an increasing requirement in higher education (HE) worldwide to deliver excellence. Benchmarking is widely used for this purpose, but methodological approaches to the creation of benchmark metrics vary greatly. Approaches require selection of factors for inclusion and subsequent calculation of benchmarks for comparison. We describe an…
Descriptors: Benchmarking, Nursing Education, Prediction, Graduation Rate
Langan, A. Mark; Harris, W. Edwin – Higher Education: The International Journal of Higher Education Research, 2019
The purpose of this study is to use machine learning and exploratory data analysis to interrogate patterns of metrics from a national-level student survey. Analysis of over 1.8 million returns detected long-term stability of the predictors of student satisfaction, with survey items relating to course management and teaching being consistently most…
Descriptors: National Surveys, Student Surveys, Research Methodology, Predictor Variables
Scheuer, Oliver; Muhlenbrock, Martin; Melis, Erica – Journal of Interactive Learning Research, 2007
Recently, there is a growing interest in the automatic analysis of learner activity in web-based learning environments. The approach and system SIAM (System for Interaction Analysis by Machine learning) presented in this article aims at helping to establish a basis for the automatic analysis of interaction data by developing a data logging and…
Descriptors: Web Based Instruction, Educational Environment, Cognitive Style, Student Behavior
Wolff, Annika; Mulholland, Paul; Zdrahal, Zdenek – Interactive Learning Environments, 2014
This paper describes an approach for supporting inquiry learning from source materials, realised and tested through a tool-kit. The approach is optimised for tasks that require a student to make interpretations across sets of resources, where opinions and justifications may be hard to articulate. We adopt a dialogue-based approach to learning…
Descriptors: Inquiry, Dialogs (Language), Feedback (Response), Web 2.0 Technologies
Tsai, Yi-Shan; Perrotta, Carlo; Gaševic, Dragan – Assessment & Evaluation in Higher Education, 2020
The emergence of personalised data technologies such as learning analytics is framed as a solution to manage the needs of higher education student populations that are growing ever more diverse and larger in size. However, the current approach to learning analytics presents tensions between increasing student agency in making learning-related…
Descriptors: Student Empowerment, Equal Education, Learning Analytics, Accountability