Learning assessment in the age of big data: Learning analytics in higher education

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online pla...

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Vydané v:	Cogent education Ročník 10; číslo 1
Hlavný autor:	Caspari-Sadeghi, Sima
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Abingdon Cogent 31.12.2023 Taylor & Francis Ltd Taylor & Francis Group
Predmet:	Academic Achievement Algorithms Big Data Blended Learning Decision Making Educational Assessment Educational research Educational Resources Educational Technology Electronic Learning Enrollment Graduation Rate Handheld Devices Higher education Influence of Technology Intelligence Learning analytics Learning Management Systems Learning Theories Management Systems MOOCs Network Analysis Online Courses Open Educational Resources Resource Allocation Science Instruction technology-enhanced assessment
ISSN:	2331-186X, 2331-186X
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Abstract	Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication applications. Meanwhile, it is acknowledged that education lacks computational infrastructure and human capacity to fully exploit the potential of big data. This paper explores the use of Learning Analytics (LA) in higher education for measurement purposes. Four main LA functions in the assessment are outlined: (a) monitoring and analysis, (b) automated feedback, (c) prediction, prevention, and intervention, and (d) new forms of assessment. The paper concludes by discussing the challenges of adopting and upscaling LA as well as the implications for instructors in higher education.
AbstractList	Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication applications. Meanwhile, it is acknowledged that education lacks computational infrastructure and human capacity to fully exploit the potential of big data. This paper explores the use of Learning Analytics (LA) in higher education for measurement purposes. Four main LA functions in the assessment are outlined: (a) monitoring and analysis, (b) automated feedback, (c) prediction, prevention, and intervention, and (d) new forms of assessment. The paper concludes by discussing the challenges of adopting and upscaling LA as well as the implications for instructors in higher education. AbstractData-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication applications. Meanwhile, it is acknowledged that education lacks computational infrastructure and human capacity to fully exploit the potential of big data. This paper explores the use of Learning Analytics (LA) in higher education for measurement purposes. Four main LA functions in the assessment are outlined: (a) monitoring and analysis, (b) automated feedback, (c) prediction, prevention, and intervention, and (d) new forms of assessment. The paper concludes by discussing the challenges of adopting and upscaling LA as well as the implications for instructors in higher education.
Author	Caspari-Sadeghi, Sima
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SubjectTerms	Academic Achievement Algorithms Big Data Blended Learning Decision Making Educational Assessment Educational research Educational Resources Educational Technology Electronic Learning Enrollment Graduation Rate Handheld Devices Higher education Influence of Technology Intelligence Learning analytics Learning Management Systems Learning Theories Management Systems MOOCs Network Analysis Online Courses Open Educational Resources Resource Allocation Science Instruction technology-enhanced assessment
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Title	Learning assessment in the age of big data: Learning analytics in higher education
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