Learning analytics in higher education: current innovations, future potential, and practical applications
Learning analytics in higher education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-know...
Gespeichert in:
| Weitere Verfasser: | , , , |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Routledge, Taylor & Francis Group
2019
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| Schlagworte: | |
| Zusammenfassung: | Learning analytics in higher education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators |
| Beschreibung: | xv, 199 pages illustrations, graphs 23 cm |
| ISBN: | 9781138302174 9781138302136 |
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| 505 | 8 | |a Absorptive capacity and routines: understanding barriers to learning analytics adoption in higher education -- Analytics in the field: why locally grown continuous improvement systems are essential for effective data-driven decision-making -- Big data, small data, and data shepherds -- Evaluating scholarly teaching: a model and call for an evidence-based approach -- Discipline-focused learning analytics approaches with users instead of for users -- Student consent in learning analytics: the devil in the details? -- Using learning analytics to improve student learning outcomes assessment: benefits, constraints, & possibilities -- Data, data everywhere: implications and considerations | |
| 520 | |a Learning analytics in higher education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators | ||
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| contents | Absorptive capacity and routines: understanding barriers to learning analytics adoption in higher education -- Analytics in the field: why locally grown continuous improvement systems are essential for effective data-driven decision-making -- Big data, small data, and data shepherds -- Evaluating scholarly teaching: a model and call for an evidence-based approach -- Discipline-focused learning analytics approaches with users instead of for users -- Student consent in learning analytics: the devil in the details? -- Using learning analytics to improve student learning outcomes assessment: benefits, constraints, & possibilities -- Data, data everywhere: implications and considerations |
| ctrlnum | (OCoLC)1056970178 (DE-599)BVBBV045229503 |
| discipline | Allgemeines |
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| id | DE-604.BV045229503 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:12:11Z |
| institution | BVB |
| isbn | 9781138302174 9781138302136 |
| language | English |
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| oclc_num | 1056970178 |
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| physical | xv, 199 pages illustrations, graphs 23 cm |
| publishDate | 2019 |
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| publisher | Routledge, Taylor & Francis Group |
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| spelling | Learning analytics in higher education current innovations, future potential, and practical applications edited by Jaime Lester, Carrie Klein, Aditya Johri and Huzefa Rangwala New York, NY Routledge, Taylor & Francis Group 2019 © 2019 xv, 199 pages illustrations, graphs 23 cm txt rdacontent n rdamedia nc rdacarrier Absorptive capacity and routines: understanding barriers to learning analytics adoption in higher education -- Analytics in the field: why locally grown continuous improvement systems are essential for effective data-driven decision-making -- Big data, small data, and data shepherds -- Evaluating scholarly teaching: a model and call for an evidence-based approach -- Discipline-focused learning analytics approaches with users instead of for users -- Student consent in learning analytics: the devil in the details? -- Using learning analytics to improve student learning outcomes assessment: benefits, constraints, & possibilities -- Data, data everywhere: implications and considerations Learning analytics in higher education provides a foundational understanding of how learning analytics is defined, what barriers and opportunities exist, and how it can be used to improve practice, including strategic planning, course development, teaching pedagogy, and student assessment. Well-known contributors provide empirical theoretical, and practical perspectives on the current use and future potential of learning analytics for student learning and data-driven decision-making, ways to effectively evaluate and research learning analytics, integration of learning analytics into practice, organizational barriers and opportunities for harnessing Big Data to create and support use of these tools, and ethical considerations related to privacy and consent. Designed to give readers a practical and theoretical foundation in learning analytics and how data can support student success in higher education, this book is a valuable resource for scholars and administrators Academic achievement / Evaluation Education, Higher / Evaluation Educational evaluation / Data processing Data mining Academic achievement / Evaluation fast Data mining fast Education, Higher / Evaluation fast Educational evaluation / Data processing fast Lester, Jaime edt Klein, Carrie edt Johri, Aditya Sonstige oth Rangwala, Huzefa edt Johri, Aditya edt Erscheint auch als Online-Ausgabe 978-0-203-73186-4 |
| spellingShingle | Learning analytics in higher education current innovations, future potential, and practical applications Absorptive capacity and routines: understanding barriers to learning analytics adoption in higher education -- Analytics in the field: why locally grown continuous improvement systems are essential for effective data-driven decision-making -- Big data, small data, and data shepherds -- Evaluating scholarly teaching: a model and call for an evidence-based approach -- Discipline-focused learning analytics approaches with users instead of for users -- Student consent in learning analytics: the devil in the details? -- Using learning analytics to improve student learning outcomes assessment: benefits, constraints, & possibilities -- Data, data everywhere: implications and considerations Academic achievement / Evaluation Education, Higher / Evaluation Educational evaluation / Data processing Data mining Academic achievement / Evaluation fast Data mining fast Education, Higher / Evaluation fast Educational evaluation / Data processing fast |
| title | Learning analytics in higher education current innovations, future potential, and practical applications |
| title_auth | Learning analytics in higher education current innovations, future potential, and practical applications |
| title_exact_search | Learning analytics in higher education current innovations, future potential, and practical applications |
| title_full | Learning analytics in higher education current innovations, future potential, and practical applications edited by Jaime Lester, Carrie Klein, Aditya Johri and Huzefa Rangwala |
| title_fullStr | Learning analytics in higher education current innovations, future potential, and practical applications edited by Jaime Lester, Carrie Klein, Aditya Johri and Huzefa Rangwala |
| title_full_unstemmed | Learning analytics in higher education current innovations, future potential, and practical applications edited by Jaime Lester, Carrie Klein, Aditya Johri and Huzefa Rangwala |
| title_short | Learning analytics in higher education |
| title_sort | learning analytics in higher education current innovations future potential and practical applications |
| title_sub | current innovations, future potential, and practical applications |
| topic | Academic achievement / Evaluation Education, Higher / Evaluation Educational evaluation / Data processing Data mining Academic achievement / Evaluation fast Data mining fast Education, Higher / Evaluation fast Educational evaluation / Data processing fast |
| topic_facet | Academic achievement / Evaluation Education, Higher / Evaluation Educational evaluation / Data processing Data mining |
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