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The Art of Modelling the Learning Pr...
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The Art of Modelling the Learning Process = Uniting Educational Research and Practice /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
The Art of Modelling the Learning Process/ by Jimmie Leppink.
其他題名:
Uniting Educational Research and Practice /
作者:
Leppink, Jimmie.
面頁冊數:
XXVII, 264 p. 69 illus., 55 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Medical Education. -
電子資源:
https://doi.org/10.1007/978-3-030-43082-5
ISBN:
9783030430825
The Art of Modelling the Learning Process = Uniting Educational Research and Practice /
Leppink, Jimmie.
The Art of Modelling the Learning Process
Uniting Educational Research and Practice /[electronic resource] :by Jimmie Leppink. - 1st ed. 2020. - XXVII, 264 p. 69 illus., 55 illus. in color.online resource. - Springer Texts in Education,2366-7672. - Springer Texts in Education,.
Part I – Common Questions -- Chapter 1: Learning Processes -- Chapter 2: Study Designs -- Chapter 3: Statistical Learning -- Chapter 4: Anchoring Narratives -- Part II – Variable Types -- Chapter 5 – Pass/Fail and Other Dichotomies -- Chapter 6 – Multicategory Nominal Choices -- Chapter 7 – Ordered Performance Categories -- Chapter 8 – Quantifiable Learning Outcomes -- Part III – Variable Networks -- Chapter 9 – Instrument Structures -- Chapter 10 – Cross-Instrument Communication -- Chapter 11 – Temporal Structures -- Chapter 12 – Longitudinal Assessment Networks -- Part IV – Time Series -- Chapter 13 – Randomised Controlled Experiments -- Chapter 14 – Static and Dynamic Group Structures -- Chapter 15 – Progress Testing in Large Cohorts -- Chapter 16 – Small Samples and Case Studies -- Part V – Conclusion -- Chapter 17: General Recommendations. .
By uniting key concepts and methods from education, psychology, statistics, econometrics, medicine, language, and forensic science, this textbook provides an interdisciplinary methodological approach to study human learning processes longitudinally. This longitudinal approach can help to acquire a better understanding of learning processes, can inform both future learning and the revision of educational content and formats, and may help to foster self-regulated learning skills. The initial section of this textbook focuses on different types of research questions as well as practice-driven questions that may refer to groups or to individual learners. This is followed by a discussion of different types of outcome variables in educational research and practice, such as pass/fail and other dichotomies, multi-category nominal choices, ordered performance categories, and different types of quantifiable (i.e., interval or ratio level of measurement) variables. For each of these types of outcome variables, single-measurement and repeated-measurements scenarios are offered with clear examples. The book then introduces cross-sectional and longitudinal interdependence of learning-related variables through emerging network-analytic methods and in the final part the learned concepts are applied to different types of studies involving time series. The book concludes with some general guidelines to give direction to future (united) educational research and practice. This textbook is a must-have for all applied researchers, teachers and practitioners interested in (the teaching of) human learning, instructional design, assessment, life-long learning or applications of concepts and methods commonly encountered in fields such as econometrics, psychology, and sociology to educational research and practice.
ISBN: 9783030430825
Standard No.: 10.1007/978-3-030-43082-5doiSubjects--Topical Terms:
677657
Medical Education.
LC Class. No.: LB1050.9-1091
Dewey Class. No.: 370.15
The Art of Modelling the Learning Process = Uniting Educational Research and Practice /
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Part I – Common Questions -- Chapter 1: Learning Processes -- Chapter 2: Study Designs -- Chapter 3: Statistical Learning -- Chapter 4: Anchoring Narratives -- Part II – Variable Types -- Chapter 5 – Pass/Fail and Other Dichotomies -- Chapter 6 – Multicategory Nominal Choices -- Chapter 7 – Ordered Performance Categories -- Chapter 8 – Quantifiable Learning Outcomes -- Part III – Variable Networks -- Chapter 9 – Instrument Structures -- Chapter 10 – Cross-Instrument Communication -- Chapter 11 – Temporal Structures -- Chapter 12 – Longitudinal Assessment Networks -- Part IV – Time Series -- Chapter 13 – Randomised Controlled Experiments -- Chapter 14 – Static and Dynamic Group Structures -- Chapter 15 – Progress Testing in Large Cohorts -- Chapter 16 – Small Samples and Case Studies -- Part V – Conclusion -- Chapter 17: General Recommendations. .
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