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Ryan, Mary; Bourke, Terri; Lane, Rod; O'Brien, Peter; L'Estrange, Lyra – Teaching Education, 2022
The recasting of accountability in teaching and teacher education as a problem of impact across many countries has seen a proliferation of policies and strategies that datify the work of students and teachers. The enactment of such policies can be interrogated from the perspectives of multiple policy actors to understand the effects of the 'impact…
Descriptors: Discourse Analysis, Foreign Countries, Accountability, Teaching Methods
Walsh, Chris; Mital, Abhinav; Ratcliff, Michael; Yap, Ana; Jamaledine, Zeina – Australasian Journal of Educational Technology, 2020
Online education often struggles to maintain a consistent, high quality academic experience. High attrition rates and low student satisfaction continue to challenge higher education providers. We present an innovative public-private partnership that delivers a resources-sufficient model of fully online postgraduate education with high levels of…
Descriptors: Partnerships in Education, Electronic Learning, Distance Education, Academic Support Services
Hassad, Rossi A. – Statistics Education Research Journal, 2020
Training programs for statisticians and data scientists in healthcare should give greater importance to fostering inductive reasoning toward developing a mindset for optimizing Big Data. This can complement the current predominant focus on the hypothetico-deductive reasoning model, and is theoretically supported by the constructivist philosophy…
Descriptors: Statistics, Data Analysis, Data Collection, Logical Thinking
Zheng, Lanqin – Lecture Notes in Educational Technology, 2021
This book highlights the importance of design in computer-supported collaborative learning (CSCL) by proposing data-driven design and assessment. It addresses data-driven design, which focuses on the processing of data and on improving design quality based on analysis results, in three main sections. The first section explains how to design…
Descriptors: Data Use, Instructional Design, Computer Assisted Instruction, Cooperative Learning
Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks
Sanguino, Juan Camilo; Manrique, Rubén; Mariño, Olga; Linares-Vásquez, Mario; Cardozo, Nicolás – Journal of Educational Data Mining, 2022
Recommender systems in educational contexts have proven to be effective in identifying learning resources that fit the interests and needs of learners. Their usage has been of special interest in online self-learning scenarios to increase student retention and improve the learning experience. In this article, we present the design of a hybrid…
Descriptors: Information Systems, Educational Resources, Independent Study, Online Courses
Dollinger, Mollie; Lodge, Jason – Educational Media International, 2019
The growing practice of students as partners (SaP) has sparked numerous conversations in higher education about the roles students do and should play in shaping the future. SaP scholars contend that by engaging with students in meaningful partnership, underpinned by values such reciprocity, students can have deeper and more meaningful learning…
Descriptors: Learning Analytics, Partnerships in Education, Student Role, Teacher Student Relationship
Sean Mackney; Robin Shields – International Perspectives on Education and Society, 2019
This chapter examines the application of learning analytics techniques within higher education -- learning analytics -- and its application in supporting "student success." Learning analytics focuses on the practice of using data about students to inform interventions aimed at improving outcomes (e.g., retention, graduation, and learning…
Descriptors: Learning Analytics, Academic Achievement, College Students, Data Use
Dipace, Anna; Loperfido, F. Feldia; Scarinci, Alessia – Research on Education and Media, 2018
This article describes Learning Analytics (LA) as a predictive and formative approach that enables the planning of educational scenarios in line with students' needs and languages in order to set a priori and in progress systems of control and inspection of the following: consistency, relevance and effectiveness of training objectives, curriculum…
Descriptors: Learning Analytics, Individualized Instruction, Curriculum Design, Student Centered Learning
West, Deborah; Luzeckyj, Ann; Toohey, Danny; Vanderlelie, Jessica; Searle, Bill – Australasian Journal of Educational Technology, 2020
Increasingly learning analytics (LA) has begun utilising staff- and student-facing dashboards capturing visualisations to present data to support student success and improve learning and teaching. The use of LA is complex, multifaceted and raises many issues for consideration, including ethical and legal challenges, competing stakeholder views and…
Descriptors: College Faculty, College Administration, Ethics, Student Attitudes
Aburizaizah, Saeed Jameel – Journal of Education and Learning, 2021
For many justifications, the collection, analysis, and use of educational data are central to the evaluation and improvement of students' progress and learning outcomes. The use of data in educational evaluation and decision making are expected to span all layers--from the institution, teachers, students, and classroom levels, providing a…
Descriptors: Data Use, Decision Making, Progress Monitoring, Learning Analytics
Barollet, Théo; Bouchez Tichadou, Florent; Rastello, Fabrice – International Educational Data Mining Society, 2021
In Intelligent Tutoring Systems (ITS), methods to choose the next exercise for a student are inspired from generic recommender systems, used, for instance, in online shopping or multimedia recommendation. As such, collaborative filtering, especially matrix factorization, is often included as a part of recommendation algorithms in ITS. One notable…
Descriptors: Intelligent Tutoring Systems, Prediction, Internet, Purchasing
Devlin, Maura; Bushey, Heather – Change: The Magazine of Higher Learning, 2019
With national graduation rates that range from 32% among open enrollment institutions to 66% among private not-for-profits, higher education institutions have a moral imperative to improve the success of their students. Interventions to support today's students must consider the student holistically, be just-in-time, and come from a…
Descriptors: Data Use, Academic Achievement, Outcomes of Education, Holistic Approach
Whalley, Brian; France, Derek; Park, Julian; Mauchline, Alice; Welsh, Katharine – Higher Education Pedagogies, 2021
The concept of the Fourth Industrial Revolution is related to a ubiquitously connected, pervasively proximate (UCaPP) world and its response to COVID-19. Pedagogies need to be aligned with institutional 'quality education' and changes in the nature of the undergraduate student intake to formulate a 'Future Educational System'. Considerations…
Descriptors: Individualized Instruction, Active Learning, COVID-19, Pandemics
Wicks, Anne; Taylor-Raymond, Justine – George W. Bush Institute, Education Reform Initiative, 2021
Determining whether a state's young people are on track for a life with opportunity is a critical -- but diffcult -- task for governors and state leaders. States can be both awash in data and unable to easily access and use that data to inform policy. State longitudinal data systems that meaningfully connect workforce, higher education, K-12, and…
Descriptors: State Legislation, Data Analysis, Learning Analytics, Longitudinal Studies

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