Mark D. Shermis, Ph.D. is a professor at the University of Akron and the principal investigator of the Hewlett Foundation-funded Automated Scoring Assessment Prize (ASAP) program.  He has published extensively on machine scoring and recently co-authored the textbook Classroom Assessment in Action with Francis DiVesta. Shermis is a fellow of the American Psychological Association (Division 5) and the American Educational Research Association.  Jill Burstein, Ph.D. is a managing principal research scientist in Educational Testing Service's Research and Development Division. Her research interests include natural language processing, automated essay scoring and evaluation, educational technology, discourse and sentiment analysis, English language learning, and writing research. She holds 13 patents for natural language processing educational technology applications. Two of her inventions are e-rater®, an automated essay evaluation application, and Language MuseSM, an instructional authoring tool for teachers of English learners.

"This Handbook does a wonderful job of filling in the blanks in our understanding of these important methods. The book provides detailed descriptions of approaches that are available for computerized scoring and empirical data on their functioning. This is an extremely valuable resource for anyone who is interested in the way these scoring procedures work. I highly recommend this book." - Mark D. Reckase, Michigan State University, USA "This excellent Handbook is edited by two of the leading researchers in Automated Essay Evaluation---Mark Shermis and Jill Burstein. The 20 chapters treat writing research, capabilities of automated scoring evaluation engines, and psychometric issues. This volume is appropriate for numerous audiences including graduate students, educators, researchers, administrators, and policy makers." - Robert L. Brennan, University of Iowa, USA "At a time when the Common Core State Standards are reshaping writing instruction and writing evaluation, this volume provides a comprehensive review of AEE and its potential for meeting complex new demands for writing." - Wayne Camara, The College Board, USA "There is no other book like this. ...As we consider offering AEE, I would buy copies for myself, my staff and my Technical Advisory Board. ...Research departments in state and local education agencies contemplating purchasing such a service would be the prime market." - Lawrence M. Rudner, Graduate Management Admission Council, USA "This book ... will become the standard reference work in the field. ... [It] is intended as a primer for audiences from diverse backgrounds ... curriculum specialists, writing instructors, psychometricians, and computational linguists." - Su Baldwin, The National Board of Medical Examiners, USA "No question, the book gives a thorough insight into the state of the art and it is a must have for all researchers working in related domains. The compilation is especially exciting for researchers and practitioners working in psychometrics, writing instruction, natural language processing and intelligent tutoring systems... AEE surely will play and increasing and prominent role in the future, which makes this book even more valuable." - Wolfgang Lenhard, Department of Psychology, University of Wurburg, Germany

• Carl Whithaus, Foreword. M. D. Shermis, J. Burstein, S. A. Bursky, Introduction to Automated Essay Evaluation. N. Elliot, A. Klobucar, Automated Essay Evaluation and the Teaching of Writing. S. C. Weigle, ESL Writing and Automated Essay Evaluation. J. Burstein, J. Tetreault, N. Madnani, The E-rater® Automated Essay Scoring System. P. W. Foltz, L. A. Streeter, K. E. Lochbaum, T. K Landauer, Implementation and Applications of the Intelligent Essay Assessor. M. T. Schultz, The Intellimetric™ Automated Essay Scoring Engine – A Review and an Application to Chinese Essay Scoring. C. S. Rich, M. C. Schneider, J. M. D’Brot, Applications of Automated Essay Evaluation in West Virginia. E. Mayfield, C. Penstein Rosé, LightSIDE: Open Source Machine Learning for Text. C. Brew, C. Leacock, c-rater: Automated Short Answer Scoring at Educational Testing Service. D. M. Williamson, Probable Cause: Developing Warrants for Automated Scoring of Essays. Y. Attali, Validity and Reliability of Automated Essay Scoring. K. L. K. Koskey, M. D. Shermis, Scaling and Norming for Automated Essay Scoring. B.Bridgeman, Human Ratings and AEE. S. M. Lottridge, E. M. Schulz, H. C. Mitzel, Using Automated Scoring to Monitor Reader Performance and Detect Reader Drift in Essay Scoring. M. Gamon, M. Chodorow, C.Leacock, J.Tetreault, Grammatical Error Detection in Automatic Essay Scoring and Feedback. J. Burstein, J. Tetreault, M. Chodorow, D. Blanchard, S. Andreyev, Automated Evaluation of Discourse Coherence Quality in Essay Writing. Jill Burstein, B. Beigman-Klebanov, N. Madnani, A. Faulkner, Automated Sentiment Analysis for Essay Evaluation. P. Deane, Covering the Construct: An approach to Automated Essay Scoring Motivated by a Socio-cognitive Framework for Defining Literacy Skills. M. D. Shermis, B. Hamner, Contrasting State-of-the-Art Automated Scoring of Essays. K. Hakuta, The Policy Turn in Current Education Reform: The Common Core State Standards and Its Linguistic Challenges and Opportunities.

Mark D. Shermis, Ph.D. is a professor at the University of Akron and the principal investigator of the Hewlett Foundation-funded Automated Scoring Assessment Prize (ASAP) program.  He has published extensively on machine scoring and recently co-authored the textbook Classroom Assessment in Action with Francis DiVesta. Shermis is a fellow of the American Psychological Association (Division 5) and the American Educational Research Association.  Jill Burstein, Ph.D. is a managing principal research scientist in Educational Testing Service's Research and Development Division. Her research interests include natural language processing, automated essay scoring and evaluation, educational technology, discourse and sentiment analysis, English language learning, and writing research. She holds 13 patents for natural language processing educational technology applications. Two of her inventions are e-rater®, an automated essay evaluation application, and Language MuseSM, an instructional authoring tool for teachers of English learners.

"This Handbook does a wonderful job of filling in the blanks in our understanding of these important methods. The book provides detailed descriptions of approaches that are available for computerized scoring and empirical data on their functioning. This is an extremely valuable resource for anyone who is interested in the way these scoring procedures work. I highly recommend this book." - Mark D. Reckase, Michigan State University, USA "This excellent Handbook is edited by two of the leading researchers in Automated Essay Evaluation---Mark Shermis and Jill Burstein. The 20 chapters treat writing research, capabilities of automated scoring evaluation engines, and psychometric issues. This volume is appropriate for numerous audiences including graduate students, educators, researchers, administrators, and policy makers." - Robert L. Brennan, University of Iowa, USA "At a time when the Common Core State Standards are reshaping writing instruction and writing evaluation, this volume provides a comprehensive review of AEE and its potential for meeting complex new demands for writing." - Wayne Camara, The College Board, USA "There is no other book like this. ...As we consider offering AEE, I would buy copies for myself, my staff and my Technical Advisory Board. ...Research departments in state and local education agencies contemplating purchasing such a service would be the prime market." - Lawrence M. Rudner, Graduate Management Admission Council, USA "This book ... will become the standard reference work in the field. ... [It] is intended as a primer for audiences from diverse backgrounds ... curriculum specialists, writing instructors, psychometricians, and computational linguists." - Su Baldwin, The National Board of Medical Examiners, USA "No question, the book gives a thorough insight into the state of the art and it is a must have for all researchers working in related domains. The compilation is especially exciting for researchers and practitioners working in psychometrics, writing instruction, natural language processing and intelligent tutoring systems... AEE surely will play and increasing and prominent role in the future, which makes this book even more valuable." - Wolfgang Lenhard, Department of Psychology, University of Wurburg, Germany

• Carl Whithaus, Foreword. M. D. Shermis, J. Burstein, S. A. Bursky, Introduction to Automated Essay Evaluation. N. Elliot, A. Klobucar, Automated Essay Evaluation and the Teaching of Writing. S. C. Weigle, ESL Writing and Automated Essay Evaluation. J. Burstein, J. Tetreault, N. Madnani, The E-rater® Automated Essay Scoring System. P. W. Foltz, L. A. Streeter, K. E. Lochbaum, T. K Landauer, Implementation and Applications of the Intelligent Essay Assessor. M. T. Schultz, The Intellimetric™ Automated Essay Scoring Engine – A Review and an Application to Chinese Essay Scoring. C. S. Rich, M. C. Schneider, J. M. D’Brot, Applications of Automated Essay Evaluation in West Virginia. E. Mayfield, C. Penstein Rosé, LightSIDE: Open Source Machine Learning for Text. C. Brew, C. Leacock, c-rater: Automated Short Answer Scoring at Educational Testing Service. D. M. Williamson, Probable Cause: Developing Warrants for Automated Scoring of Essays. Y. Attali, Validity and Reliability of Automated Essay Scoring. K. L. K. Koskey, M. D. Shermis, Scaling and Norming for Automated Essay Scoring. B.Bridgeman, Human Ratings and AEE. S. M. Lottridge, E. M. Schulz, H. C. Mitzel, Using Automated Scoring to Monitor Reader Performance and Detect Reader Drift in Essay Scoring. M. Gamon, M. Chodorow, C.Leacock, J.Tetreault, Grammatical Error Detection in Automatic Essay Scoring and Feedback. J. Burstein, J. Tetreault, M. Chodorow, D. Blanchard, S. Andreyev, Automated Evaluation of Discourse Coherence Quality in Essay Writing. Jill Burstein, B. Beigman-Klebanov, N. Madnani, A. Faulkner, Automated Sentiment Analysis for Essay Evaluation. P. Deane, Covering the Construct: An approach to Automated Essay Scoring Motivated by a Socio-cognitive Framework for Defining Literacy Skills. M. D. Shermis, B. Hamner, Contrasting State-of-the-Art Automated Scoring of Essays. K. Hakuta, The Policy Turn in Current Education Reform: The Common Core State Standards and Its Linguistic Challenges and Opportunities.

Mark D. Shermis, Ph.D. is a professor at the University of Akron and the principal investigator of the Hewlett Foundation-funded Automated Scoring Assessment Prize (ASAP) program.  He has published extensively on machine scoring and recently co-authored the textbook Classroom Assessment in Action with Francis DiVesta. Shermis is a fellow of the American Psychological Association (Division 5) and the American Educational Research Association.  Jill Burstein, Ph.D. is a managing principal research scientist in Educational Testing Service's Research and Development Division. Her research interests include natural language processing, automated essay scoring and evaluation, educational technology, discourse and sentiment analysis, English language learning, and writing research. She holds 13 patents for natural language processing educational technology applications. Two of her inventions are e-rater®, an automated essay evaluation application, and Language MuseSM, an instructional authoring tool for teachers of English learners.

"This Handbook does a wonderful job of filling in the blanks in our understanding of these important methods. The book provides detailed descriptions of approaches that are available for computerized scoring and empirical data on their functioning. This is an extremely valuable resource for anyone who is interested in the way these scoring procedures work. I highly recommend this book." - Mark D. Reckase, Michigan State University, USA "This excellent Handbook is edited by two of the leading researchers in Automated Essay Evaluation---Mark Shermis and Jill Burstein. The 20 chapters treat writing research, capabilities of automated scoring evaluation engines, and psychometric issues. This volume is appropriate for numerous audiences including graduate students, educators, researchers, administrators, and policy makers." - Robert L. Brennan, University of Iowa, USA "At a time when the Common Core State Standards are reshaping writing instruction and writing evaluation, this volume provides a comprehensive review of AEE and its potential for meeting complex new demands for writing." - Wayne Camara, The College Board, USA "There is no other book like this. ...As we consider offering AEE, I would buy copies for myself, my staff and my Technical Advisory Board. ...Research departments in state and local education agencies contemplating purchasing such a service would be the prime market." - Lawrence M. Rudner, Graduate Management Admission Council, USA "This book ... will become the standard reference work in the field. ... [It] is intended as a primer for audiences from diverse backgrounds ... curriculum specialists, writing instructors, psychometricians, and computational linguists." - Su Baldwin, The National Board of Medical Examiners, USA "No question, the book gives a thorough insight into the state of the art and it is a must have for all researchers working in related domains. The compilation is especially exciting for researchers and practitioners working in psychometrics, writing instruction, natural language processing and intelligent tutoring systems... AEE surely will play and increasing and prominent role in the future, which makes this book even more valuable." - Wolfgang Lenhard, Department of Psychology, University of Wurburg, Germany

• Carl Whithaus, Foreword. M. D. Shermis, J. Burstein, S. A. Bursky, Introduction to Automated Essay Evaluation. N. Elliot, A. Klobucar, Automated Essay Evaluation and the Teaching of Writing. S. C. Weigle, ESL Writing and Automated Essay Evaluation. J. Burstein, J. Tetreault, N. Madnani, The E-rater® Automated Essay Scoring System. P. W. Foltz, L. A. Streeter, K. E. Lochbaum, T. K Landauer, Implementation and Applications of the Intelligent Essay Assessor. M. T. Schultz, The Intellimetric™ Automated Essay Scoring Engine – A Review and an Application to Chinese Essay Scoring. C. S. Rich, M. C. Schneider, J. M. D’Brot, Applications of Automated Essay Evaluation in West Virginia. E. Mayfield, C. Penstein Rosé, LightSIDE: Open Source Machine Learning for Text. C. Brew, C. Leacock, c-rater: Automated Short Answer Scoring at Educational Testing Service. D. M. Williamson, Probable Cause: Developing Warrants for Automated Scoring of Essays. Y. Attali, Validity and Reliability of Automated Essay Scoring. K. L. K. Koskey, M. D. Shermis, Scaling and Norming for Automated Essay Scoring. B.Bridgeman, Human Ratings and AEE. S. M. Lottridge, E. M. Schulz, H. C. Mitzel, Using Automated Scoring to Monitor Reader Performance and Detect Reader Drift in Essay Scoring. M. Gamon, M. Chodorow, C.Leacock, J.Tetreault, Grammatical Error Detection in Automatic Essay Scoring and Feedback. J. Burstein, J. Tetreault, M. Chodorow, D. Blanchard, S. Andreyev, Automated Evaluation of Discourse Coherence Quality in Essay Writing. Jill Burstein, B. Beigman-Klebanov, N. Madnani, A. Faulkner, Automated Sentiment Analysis for Essay Evaluation. P. Deane, Covering the Construct: An approach to Automated Essay Scoring Motivated by a Socio-cognitive Framework for Defining Literacy Skills. M. D. Shermis, B. Hamner, Contrasting State-of-the-Art Automated Scoring of Essays. K. Hakuta, The Policy Turn in Current Education Reform: The Common Core State Standards and Its Linguistic Challenges and Opportunities.