Cheating lessons : learning from academic dishonesty / James M. Lang.
Material type: TextPublisher: Cambridge, Massachusetts : Harvard University Press, 2013Copyright date: ©2013Description: viii, 256 pages ; 22 cmContent type:- text
- unmediated
- volume
- 0674724631
- 9780674724631
- 371.58 23
- LB3609 .L275 2013
Item type | Current library | Call number | Copy number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|
Book | North Campus North Campus Main Collection | 371.58 LAN (Browse shelf(Opens below)) | 1 | Available | A549460B | ||
Book | South Campus South Campus Main Collection | 371.58 LAN (Browse shelf(Opens below)) | 1 | Available | A549462B |
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Includes bibliographical references and index.
Introduction -- Who cheats-and how much? -- Case studies in (the history of) cheating -- "Fudging" learning environments -- Fostering intrinsic motivation -- Learning for mastery -- Lowering stakes -- Instilling self-efficacy -- Cheating on campus -- On original work -- Responding to cheating -- Cheating in your classroom -- Conclusion: The future of cheating.
Nearly three-quarters of college students cheat during their undergraduate careers, a startling number attributed variously to the laziness of today's students, their lack of a moral compass, or the demands of a hypercompetitive society. For the author, cultural or sociological explanations like these are red herrings. His provocative new research indicates that students often cheat because their learning environments give them ample incentives to try, and that strategies which make cheating less worthwhile also improve student learning. This book is a practical guide to tackling academic dishonesty at its roots. Drawing on an array of findings from cognitive theory, he analyzes the specific, often hidden features of course design and daily classroom practice that create opportunities for cheating. Courses that set the stakes of performance very high, that rely on single assessment mechanisms like multiple-choice tests, that have arbitrary grading criteria: these are the kinds of conditions that breed cheating. He seeks to empower teachers to create more effective learning environments that foster intrinsic motivation, promote mastery, and instill the sense of self-efficacy that students need for deep learning. Although cheating is a persistent problem, the prognosis is not dire. The good news is that strategies which reduce cheating also improve student performance overall. Instructors who learn to curb academic dishonesty will have done more than solve a course management problem; they will have become better educators all around.
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