The Art of Modelling the Learning Process

1. Front Matter

   Pages i-xxvii

   PDF

2. Common Questions

   1. Front Matter

      Pages 1-1

      PDF

   2. Learning Processes

      • Jimmie Leppink

      Pages 3-19

   3. Study Designs

      • Jimmie Leppink

      Pages 21-34

   4. Statistical Learning

      • Jimmie Leppink

      Pages 35-65

   5. Anchoring Narratives

      • Jimmie Leppink

      Pages 67-80

3. Variable Types

   1. Front Matter

      Pages 81-81

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   2. Pass/Fail and Other Dichotomies

      • Jimmie Leppink

      Pages 83-102

   3. Multicategory Nominal Choices

      • Jimmie Leppink

      Pages 103-110

   4. Ordered Performance Categories

      • Jimmie Leppink

      Pages 111-120

   5. Quantifiable Learning Outcomes

      • Jimmie Leppink

      Pages 121-132

4. Variable Networks

   1. Front Matter

      Pages 133-133

      PDF

   2. Instrument Structures

      • Jimmie Leppink

      Pages 135-157

   3. Cross-Instrument Communication

      • Jimmie Leppink

      Pages 159-172

   4. Temporal Structures

      • Jimmie Leppink

      Pages 173-179

   5. Longitudinal Assessment Networks

      • Jimmie Leppink

      Pages 181-191

5. Time Series

   1. Front Matter

      Pages 193-193

      PDF

   2. Randomised Controlled Experiments

      • Jimmie Leppink

      Pages 195-207

   3. Static and Dynamic Group Structures

      • Jimmie Leppink

      Pages 209-226

   4. Progress Testing in Larger Cohorts

      • Jimmie Leppink

      Pages 227-233

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 typesof 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.

• Learning Process(es)
• Educational Research
• Experimental Research in Education
• Small-sample Research in Education
• Case Studies in Education
• Statistical Learning in Education
• Statistical Testing and Estimation
• Decision-making in Education
• Assessment in Education
• Longitudinal Assessment
• Educational Measurement
• Social Network Analysis
• Dynamic Networks in Education
• Progress Testing
• Time Series Analysis
• learning and instruction

“In The Art of Modeling the Learning Process, Dr. Jimmie Leppink offers a contemporary view on the design and execution of studies of how and why individuals learn. This book is incredibly timely, as recent advances in analytic methods and theories have opened the door to new ways to explore knowledge acquisition and behavioral change over time. Dr. Leppink begins by highlighting, in easy to understand language, types of questions one might ask about the learning process, and demonstrates how to express them via a range of research methodologies that account for common issues such as missing data. He then maps this process onto multiple types of data that one might generate or collect in real-world studies, before expanding these examples into novel network-analytic and longitudinal frameworks. I highly recommend this book to students and applied researchers in the science of learning.” (Dr. M. Shane Tutwiler, Assistant Professor of Educational Foundations, University of Rhode Island, USA)

• Hull York Medical School, University of York, York, UK

  Jimmie Leppink

Jimmie Leppink (28 April 1983) obtained degrees in Psychology (MSc, September 2005 – July 2006, Cum Laude), Law (LLM, September 2007 – July 2008), and Statistics Education (PhD, September 2008 – March 2012) from Maastricht University, the Netherlands, and obtained a degree in Statistics (MSc, October 2011 – July 2012, Magna Cum Laude) from the Catholic University of Leuven, Belgium. He defended his PhD Thesis in Statistics Education in June of 2012, and was a Postdoc in Education (April 2012 – March 2017) and Assistant Professor of Methodology and Statistics (April 2017 – January 2019) at Maastricht University’s School of Health Professions Education. Since January 2019, he has been working as a Senior Lecturer in Medical Education at Hull York Medical School, which is a joint medical school of the University of Hull and the University of York. His research, teaching, and consulting activities revolve around applications of quantitative methods in Education, Psychology, and a broader Social Science context as well as the use of learning analytics for the design of learning environments, instruction, and assessment in Medical Education and the broader Higher Education.

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