Skip to main content Accessibility help
×
Hostname: page-component-7b7567c8c-kwt9d Total loading time: 0 Render date: 2026-11-13T17:20:27.085Z Has data issue: false hasContentIssue false

16 - Development of Numerical Knowledge

from Subpart II.2 - Childhood and Adolescence: The Development of Human Thinking

Published online by Cambridge University Press:  24 February 2022

By
Robert S. Siegler
Edited by
Olivier Houdé and
Grégoire Borst
Olivier Houdé
Affiliation:
Université de Paris V
Grégoire Borst
Affiliation:
Université de Paris V
Get access

Summary

Numerical knowledge is of great and growing importance. While children are attending school, numerical knowledge is essential for learning more advanced mathematics and science, and eventually for learning computer science, psychology, sociology, economics, and a host of other subjects. After children leave school, numerical knowledge is essential not just in STEM areas but also in a wide range of other occupations. Illustratively, a survey of more than 2,000 employed people in the United States, chosen through random digit dials, indicated that 94 percent reported using math in their work, including majorities in occupations classified as upper white collar, lower white collar, upper blue collar, and lower blue collar (Handel, 2016). Moreover, numerical proficiency is related to occupational success: numerical knowledge at age seven years predicts SES at age forty-two years, even after statistically controlling for IQ, years of education, reading skill, working memory, race, and family SES (Ritchie & Bates, 2013).

Information

Type
Chapter
Information
The Cambridge Handbook of Cognitive Development , pp. 361 - 382
Publisher: Cambridge University Press
Print publication year: 2022

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Book purchase

Temporarily unavailable

References

Agrillo, C., Piffer, L., Bisazza, A., & Butterworth, B. (2012). Evidence for two numerical systems that are similar in humans and guppies. PLoS ONE, 7, e31923.CrossRefGoogle ScholarPubMed
Alibali, M. W., & Goldin-Meadow, S. (1993). Gesture-speech mismatch and mechanisms of learning: What the hands reveal about a child’s state of mind. Cognitive Psychology, 25, 468–523.CrossRefGoogle ScholarPubMed
Andres, M., Michaux, N., & Pesenti, M. (2012). Common substrate for mental arithmetic and finger representation in the parietal cortex. NeuroImage, 62, 1520–1528.CrossRefGoogle ScholarPubMed
Ashcraft, M. H. (1982). The development of mental arithmetic: A chronometric approach. Developmental Review, 2, 213–236.CrossRefGoogle Scholar
Bailey, D. H., Siegler, R. S., & Geary, D. C. (2014). Early predictors of middle school fraction knowledge. Developmental Science, 17, 775–785.CrossRefGoogle ScholarPubMed
Baroody, A. J., & Dowker, A. (eds.) (2003). The Development of Arithmetic Concepts and Skills: Constructing Adaptive Expertise. Mahwah, NJ: Erlbaum.Google Scholar
Berteletti, I., & Booth, J. R. (2015). Perceiving fingers in single-digit arithmetic problems. Frontiers in Psychology, 6, 226.CrossRefGoogle ScholarPubMed
Berteletti, I., Lucangeli, D., Piazza, M., Dehaene, S., & Zorzi, M. (2010). Numerical estimation in preschoolers. Developmental Psychology, 41, 545–551.CrossRefGoogle Scholar
Binet, A., & Simon, T. (1905). New methods for the diagnosis of the intellectual level of subnormals. L’Année Psychologique, 11, 191–244. Translated by Elizabeth S. Kite and reprinted in The Development of Intelligence in Children (1916). Baltimore: Williams & Wilkins.CrossRefGoogle Scholar
Braithwaite, D. W., Pyke, A. A., & Siegler, R. S. (2017). A computational model of fraction arithmetic. Psychological Review, 124, 603–625.CrossRefGoogle ScholarPubMed
Braithwaite, D. W., Tian, J., & Siegler, R. S. (2018). Do children understand fraction addition? Developmental Science, 21, e12601.CrossRefGoogle ScholarPubMed
Brannon, E. M., & Merritt, D. J. (2011). Evolutionary foundations of the approximate number system. In Dehaene, S., & Brannon, E. (eds.), Space, Time and Number in the Brain: Searching for the Foundations of Mathematical Thought (pp. 207–224). New York: Elsevier.CrossRefGoogle Scholar
Brown, J. S., & Van Lehn, K. (1982). Toward a generative theory of “bugs.” In Carpenter, T. P., Moser, J. M., & Romberg, T. A. (eds.), Addition and Subtraction: A Cognitive Perspective (pp. 117–136). Hillsdale, N.J.: ErlbaumGoogle Scholar
Campbell, J. I., & Xue, Q. (2001). Cognitive arithmetic across cultures. Journal of Experimental Psychology. General, 130, 299–315.CrossRefGoogle ScholarPubMed
Carpenter, T. P., Corbitt, M. K., Kepner, H. S., Lindquist, M. M., & Reys, R. E. (1981). Results and Implications from the Second Mathematics Assessment of the National Assessment of Educational Progress. Reston, VA: National Council of Teachers of Mathematics.Google Scholar
Case, R., & Okamoto, Y. (1996). The role of central conceptual structures in the development of children’s thought. Monographs of the Society for Research in Child Development, 61, Nos. 1–2 (Serial No. 246).CrossRefGoogle Scholar
Chen, Q., & Li, J. (2014). Association between individual differences in nonsymbolic number acuity and math performance: A meta-analysis. Acta Psychologica, 148, 163–172.CrossRefGoogle ScholarPubMed
College Board. (2015). Advanced Placement Physics 1 Equations, Effective 2015 (pdf document). Available from https://secure-media.collegeboard.org/digitalServices/pdf/ap/ap-physics-1-equations-table.pdf. Last accessed August 2, 2021.Google Scholar
Cordes, S., & Brannon, E. M. (2008). Quantitative competencies in infancy. Developmental Science, 11, 803–808.CrossRefGoogle ScholarPubMed
Dehaene, S. (2011). The Number Sense: How the Mind Creates Mathematics. New York: Oxford University Press.Google Scholar
Depaepe, F., Torbeyns, J., Vermeersch, N., Janssens, D., Janssen, R., Kelchtermans, G., … Van Dooren, W. (2015). Teachers’ content and pedagogical content knowledge on rational numbers: A comparison of prospective elementary and lower secondary school teachers. Teaching and Teacher Education, 47, 82–92.CrossRefGoogle Scholar
Dotan, D., & Dehaene, S. (2013). How do we convert a number into a finger trajectory? Cognition, 129, 512–529.CrossRefGoogle Scholar
Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., … Japel, C. (2007). School readiness and later achievement. Developmental Psychology, 43, 1428–1446.CrossRefGoogle ScholarPubMed
Fazio, L. K., Bailey, D. H., Thompson, C. A., & Siegler, R. S. (2014). Relations of different types of numerical magnitude representations to each other and to mathematics achievement. Journal of Experimental Child Psychology, 123, 53–72.CrossRefGoogle ScholarPubMed
Gauvain, M. (2001). The Social Context of Cognitive Development. New York: The Guilford Press.Google Scholar
Geary, D. C. (2006). Development of mathematical understanding. In Kuhn, D., & Siegler, R. S. (vol. eds.), Cognition, Perception, and Language, (pp. 777–810). W. Damon (gen. ed.), Handbook of child psychology (6th ed.). New York: John Wiley & Sons.Google Scholar
Geary, D. C. (2008). An evolutionarily informed education science. Educational Psychologist, 43, 179–195.CrossRefGoogle Scholar
Geary, D. C., Hoard, M. K., Byrd-Craven, J., Nugent, L., & Numtee, C. (2007). Cognitive mechanisms underlying achievement deficits in children with mathematical learning disability. Child Development, 78, 1343–1359.CrossRefGoogle ScholarPubMed
Geary, D. C., & vanMarle, K. (2016). Young children’s core symbolic and non-symbolic quantitative knowledge in the prediction of later mathematics achievement. Developmental Psychology, 52, 2130–2144.CrossRefGoogle Scholar
Halberda, J., & Feigenson, L. (2008). Developmental change in the acuity of the “Number sense”: The approximate number system in 3-, 4-, 5-, and 6-year-olds and adults. Developmental Psychology, 44, 1457–1465.CrossRefGoogle ScholarPubMed
Halberda, J., Ly, R., Wilmer, J. B., Naiman, D. Q., & Germine, L. (2012). Number sense across the lifespan as revealed by a massive Internet-based sample. Proceedings of the National Academy of Sciences (USA), 109, 11116–11120.CrossRefGoogle ScholarPubMed
Halberda, J., Mazzocco, M. M. M., & Feigenson, L. (2008). Individual differences in non-verbal number acuity correlates with math achievement. Nature, 455, 665–668.CrossRefGoogle Scholar
Handel, M. J. (2016). What do people do at work? A profile of U.S. jobs from the survey of workplace Skills, Technology, and Management Practices (STAMP). Journal for Labour Market Research, 49, 177–197.CrossRefGoogle Scholar
Hanushek, E. A. (2016). What matters for student achievement: Updating Coleman on the influence of families and schools. EducationNext, 16 , 23–30.Google Scholar
Iuculano, T., & Butterworth, B. (2011). Understanding the real value of fractions and decimals. The Quarterly Journal of Experimental Psychology, 64, 2088–2098.CrossRefGoogle ScholarPubMed
Jordan, N. C., Hansen, N., Fuchs, L. S., Siegler, R. S., Gersten, R., & Micklos, D. (2013). Developmental predictors of fraction concepts and procedures. Journal of Experimental Child Psychology, 116, 45–58.CrossRefGoogle ScholarPubMed
Jordan, N.C., Kaplan, D., Olah, L. N., & Locuniak, M. N. (2006). Number sense growth in kindergarten: A longitudinal investigation of children at risk for mathematics difficulties. Child Development, 77, 153–175.CrossRefGoogle ScholarPubMed
Kant, I. (1781/2003). Critique of Pure Reason, trans. J. M. D. Meiklejohn. Mineola, NY: Dover.Google Scholar
Klahr, D., & MacWhinney, B. (1998). Information processing. In Damon, W. (Series ed.) & Kuhn, D. & Siegler, R. S. (vol. eds.), Handbook of Child Psychology: Vol. 2: Cognition, Perception & Language. (5th ed., pp. 631–678). New York: Wiley.Google Scholar
Le Corre, M., & Carey, S. (2007). One, two, three, four, nothing more: An investigation of the conceptual sources of the verbal counting principles. Cognition, 105, 395–438.CrossRefGoogle ScholarPubMed
LeFevre, J. A., Sadesky, G. S., & Bisanz, J. (1996). Selection of procedures in mental addition: Reassessing the problem-size effect in adults. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22, 216–230.Google Scholar
LeFevre, J. A., Smith-Chant, B. L., Hiscock, K., Dale, K. E., & Morris, J. (2003). Young adults’ strategic choices in simple arithmetic: Implications for the development of mathematical representations. In Baroody, A. J., & Dowker, A. (eds.), The Development of Arithmetic Concepts and Skills: Constructing Adaptive Expertise (pp. 203–228). Mahwah, NJ: Erlbaum.Google Scholar
Lemaire, P., & Siegler, R. S. (1995). Four aspects of strategic change: Contributions to children’s learning of multiplication. Journal of Experimental Psychology: General, 124, 83–97.CrossRefGoogle ScholarPubMed
Libertus, M., Feigenson, L., & Halberda, J. (2011). Preschool acuity of the approximate number system correlates with school math ability. Developmental Science, 14, 1292–1300.CrossRefGoogle ScholarPubMed
Lortie-Forgues, H., & Siegler, R. S. (2017). Conceptual knowledge of decimal arithmetic. Journal of Educational Psychology, 109, 374–386.CrossRefGoogle Scholar
Lortie-Forgues, H., Tian, J., & Siegler, R. S. (2015). Why is learning fraction and decimal arithmetic so difficult? Developmental Review, 38, 201–221.CrossRefGoogle Scholar
Luo, F., Lo, J., & Leu, Y. (2011). Fundamental fraction knowledge of pre-service elementary teachers: A cross-national study in the United States and Taiwan. School Science and Mathematics, 111, 164–177.CrossRefGoogle Scholar
Lyons, I. M., Price, G. R., Vaessen, A., Blomert, L., & Ansari, D. (2014). Numerical predictors of arithmetic success in grades 1-6. Developmental Science, 17, 714–726.CrossRefGoogle ScholarPubMed
Ma, L. (1999). Knowing and Teaching Elementary Mathematics: Teachers Understanding of Fundamental Mathematics in China and the United States. Mahwah, NJ: Erlbaum.CrossRefGoogle Scholar
McCrink, K., & Wynn, K. (2004). Large-number addition and subtraction by 9-month-old infants. Psychological Science, 15, 776–781.CrossRefGoogle ScholarPubMed
McCrink, K., & Wynn, K. (2007). Ratio abstraction by 6-month-old infants. Psychological Science, 18, 740–745.CrossRefGoogle Scholar
McNeil, N. M. (2014). A change-resistance account of children’s difficulties understanding mathematical equivalence. Child Development Perspectives, 8, 42–47.CrossRefGoogle Scholar
Meert, G., Grégoire, J., & Noël, M.-P. (2010). Comparing the magnitude of two fractions with common components: Which representations are used by 10- and 12-year-olds? Journal of Experimental Child Psychology, 107, 244–259.CrossRefGoogle ScholarPubMed
Miller, P. H., & Seier, W. L. (1994). Strategy utilization deficiencies in children: When, where, and why. In Reese, H. W. (ed.), Advances in Child Development and Behavior (Vol. 25, pp. 108–156). New York: Academic Press.Google Scholar
Möhring, W., Liu, R., & Libertus, M. E. (2017). Infants’ speed discrimination: Effects of different ratios and spatial orientations. Infancy, 22, 762–777.CrossRefGoogle Scholar
National Mathematics Advisory Panel. (2008). Foundations for Success: The Final Report of the National Mathematics Advisory Panel. Washington, DC: US Department of Education.Google Scholar
Ni, Y., & Zhou, Y.-D. (2005). Teaching and learning fraction and rational numbers: The origins and implications of whole number bias. Educational Psychologist, 40, 27–52.CrossRefGoogle Scholar
Nieder, A., & Dehaene, S. (2009). Representation of number in the brain. Annual Review of Neuroscience, 32, 185–208.CrossRefGoogle ScholarPubMed
Park, J., Park, D. C., & Polk, T. A. (2013). Parietal functional connectivity in numerical cognition. Cerebral Cortex, 23, 2127–2135.CrossRefGoogle ScholarPubMed
Parnas, M., Lin, A. C., Huetteroth, W., & Miesenböck, G. (2013). Odor discrimination in Drosophila: From neural population codes to behavior. Neuron, 79, 932–944.CrossRefGoogle ScholarPubMed
Piaget, J. (1952). The Child’s Concept of Number. New York: W. W. Norton.Google Scholar
Piazza, M. (2011). Neurocognitive start-up tools for symbolic number representations. In Dehaene, S., & Brannon, E. (eds.), Space, Time, and Number in the Brain: Searching for the Foundations of Mathematical Thought (pp. 267–285). London: Elsevier.CrossRefGoogle Scholar
Piffer, L., Petrazzini, M. E. M., & Agrillo, C. (2013). Large number discrimination in newborn fish. PLoS ONE, 8, e62466.CrossRefGoogle ScholarPubMed
Ramani, G. B., & Siegler, R. S. (2008). Promoting broad and stable improvements in low-income children’s numerical knowledge through playing number board games. Child Development, 79, 375–394.CrossRefGoogle ScholarPubMed
Ramani, G. B., & Siegler, R. S. (2011). Reducing the gap in numerical knowledge between low- and middle-income preschoolers. Journal of Applied Developmental Psychology, 32, 146–159.CrossRefGoogle Scholar
Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. In Duncan, G., & Murnane, R. (eds.), Whither Opportunity? Rising Inequality and the Uncertain Life Chances of Low-Income Children (pp. 91–116). New York: Russell Sage Foundation Press.Google Scholar
Reeve, R. A., Paul, J. M., & Butterworth, B. (2015). Longitudinal changes in young children’s 0–100 to 0–1000 number-line error signatures. Frontiers in Psychology, 6, Article 647.Google ScholarPubMed
Resnick, I., Jordan, N. C., Hansen, N., Rajan, V., Rodrigues, J., Siegler, R. S., & Fuchs, L. (2016). Developmental growth trajectories in understanding of fraction magnitude from fourth through sixth grade. Developmental Psychology, 52, 746–757.CrossRefGoogle ScholarPubMed
Resnick, L. B., Nesher, P., Leonard, F., Magone, M., Omanson, S., & Peled, I. (1989). Conceptual bases of arithmetic errors: The case for decimal fractions. Journal for Research in Mathematics Education, 20, 8–27.CrossRefGoogle Scholar
Riggs, K. J., Ferrand, L., Lancelin, D., Fryziel, L., Dumur, G., & Simpson, A. (2006). Subitizing in tactile perception. Psychological Science, 17, 271–272.CrossRefGoogle ScholarPubMed
Ritchie, S. J., & Bates, T. C. (2013). Enduring links from childhood mathematics and reading achievement to adult socioeconomic status. Psychological Science, 24, 1301–1308.CrossRefGoogle ScholarPubMed
Robinson, K. M. (2017). The understanding of additive and multiplicative arithmetic concepts. In Geary, D. C., Berch, D. B., Ochsendorf, R., & Mann Koepke, K. (eds.). Acquiring Complex Arithmetic Skills and Higher-Order Mathematical Concepts (Vol. 3, Mathematical Cognition and Learning, pp. 21–46). San Diego, CA: Elsevier Academic Press.CrossRefGoogle Scholar
Schneider, M., Beeres, K., Coban, L., Merz, S., Schmidt, S., Stricker, J., & De Smedt, B. (2017). Associations of non-symbolic and symbolic numerical magnitude processing with mathematical competence: A meta-analysis. Developmental Science, 20, e12372.CrossRefGoogle ScholarPubMed
Schneider, M., Merz, S., Stricker, J., De Smedt, B., Torbeyns, J., Verschaffel, L., & Luwel, K. (2018). Associations of number line estimation with mathematical competence: A meta-analysis. Child Development, 89, 1467–1484.CrossRefGoogle ScholarPubMed
Schneider, M., & Siegler, R. S. (2010). Representations of the magnitudes of fractions. Journal of Experimental Psychology: Human Perception and Performance, 36, 1227–1238.Google ScholarPubMed
Shrager, J., & Siegler, R. S. (1998). SCADS: A model of children’s strategy choices and strategy discoveries. Psychological Science, 9, 405–410.CrossRefGoogle Scholar
Siegler, R. S. (1987). The perils of averaging data over strategies: An example from children’s addition. Journal of Experimental Psychology: General, 116, 250–264.CrossRefGoogle Scholar
Siegler, R. S. (1988). Strategy choice procedures and the development of multiplication skill. Journal of Experimental Psychology: General, 117, 258–275.CrossRefGoogle ScholarPubMed
Siegler, R. S. (1989). Hazards of mental chronometry: An example from children’s subtraction. Journal of Educational Psychology, 81, 497–506.CrossRefGoogle Scholar
Siegler, R. S. (1996). Unidimensional thinking, multidimensional thinking, and characteristic tendencies of thought. In Sameroff, A. J., & Haith, M. M. (eds.), The Five to Seven Year Shift: The Age of Reason and Responsibility (pp. 63–84). Chicago, IL: University of Chicago Press.Google Scholar
Siegler, R. S. (2006). Microgenetic analyses of learning. In Damon, W., & Lerner, R. M. (Series eds.) & Kuhn, D. & Siegler, R. S. (vol. eds.), Handbook of Child Psychology: Volume 2: Cognition, Perception, and Language (6th ed., pp. 464–510). Hoboken, NJ: Wiley.Google Scholar
Siegler, R. S. (2016). Magnitude knowledge: The common core of numerical development. Developmental Science, 19, 341–361.CrossRefGoogle ScholarPubMed
Siegler, R. S., & Booth, J. L. (2004). Development of numerical estimation in young children. Child Development, 75, 428–444.CrossRefGoogle ScholarPubMed
Siegler, R. S., & Braithwaite, D. W. (2017). Numerical development. Annual Review of Psychology, 68, 187–213.CrossRefGoogle ScholarPubMed
Siegler, R. S., & Crowley, K. (1994). Constraints on learning in non-privileged domains. Cognitive Psychology, 27, 194–227.CrossRefGoogle Scholar
Siegler, R. S., Duncan, G. J., Davis-Kean, P. E., Duckworth, K., Claessens, A., Engel, M., … Chen, M. (2012). Early predictors of high school mathematics achievement. Psychological Science, 23, 691–697.CrossRefGoogle ScholarPubMed
Siegler, R. S., & Jenkins, E. A. (1989). How Children Discover New Strategies. Hillsdale, NJ: Erlbaum.Google Scholar
Siegler, R. S., & Lemaire, P. (1997). Older and younger adults’ strategy choices in multiplication: Testing predictions of ASCM via the choice/no-choice method. Journal of Experimental Psychology: General, 126, 71–92.CrossRefGoogle Scholar
Siegler, R. S., & Lortie-Forgues, H. (2015). Conceptual knowledge of fraction arithmetic. Journal of Educational Psychology, 107, 909–918.CrossRefGoogle Scholar
Siegler, R. S., & Pyke, A. A. (2013). Developmental and individual differences in understanding fractions. Developmental Psychology, 49, 1994–2004.CrossRefGoogle ScholarPubMed
Siegler, R. S., & Ramani, G. B. (2009). Playing linear number board games – but not circular ones – improves low-income preschoolers’ numerical understanding. Journal of Educational Psychology, 101, 545–560.CrossRefGoogle Scholar
Siegler, R. S., & Shrager, J. (1984). Strategy choices in addition and subtraction: How do children know what to do? In Sophian, C. (ed.), The Origins of Cognitive Skills (pp. 229–293). Hillsdale, NJ: Erlbaum.Google Scholar
Siegler, R. S., Thompson, C. A., & Schneider, M. (2011). An integrated theory of whole number and fractions development. Cognitive Psychology, 62, 273–296.CrossRefGoogle ScholarPubMed
Spelke, E. S., & Kinzler, K. D. (2007). Core knowledge. Developmental Science, 10, 89–96.CrossRefGoogle ScholarPubMed
Sullivan, J., & Barner, D. (2014). The development of structural analogy in number-line estimation. Journal of Experimental Child Psychology, 128, 171–189.CrossRefGoogle ScholarPubMed
Svenson, O., & Sjöberg, K. (1983). Evolution of cognitive processes for solving simple additions during the first three school years. Scandinavian Journal of Psychology, 24, 117–124.CrossRefGoogle Scholar
Thompson, C. A., & Opfer, J. E. (2010). How 15 hundred is like 15 cherries: Effect of progressive alignment on representational changes in numerical cognition. Child Development, 81, 1768–1786.CrossRefGoogle ScholarPubMed
Torbeyns, J., Schneider, M., Xin, Z. & Siegler, R. S. (2015). Bridging the gap: Fraction understanding is central to mathematics achievement in students from three different continents. Learning and Instruction, 37, 5–13.CrossRefGoogle Scholar
Verschaffel, L., Greer, B., & De Corte, E. (2007). Whole number concepts and operations. In Lester, F. (ed.), Second Handbook of Research on Mathematics Teaching and Learning (pp. 557–628). Charlotte, NC: Information Age.Google Scholar
Watts, T. W., Duncan, G. J., Siegler, R. S., & Davis-Kean, P. E. (2014). What’s past is prologue: Relations between early mathematics knowledge and high school achievement. Educational Researcher, 43, 352–360.CrossRefGoogle ScholarPubMed
Wynn, K. (1992). Addition and subtraction by human infants. Nature, 358, 749–750.CrossRefGoogle ScholarPubMed
Xu, X., Chen, C., Pan, M., & Li, N. (2013). Development of numerical estimation in Chinese preschool children. Journal of Experimental Child Psychology, 116, 351–366.CrossRefGoogle ScholarPubMed

Accessibility standard: Unknown

Why this information is here

This section outlines the accessibility features of this content - including support for screen readers, full keyboard navigation and high-contrast display options. This may not be relevant for you.

Accessibility Information

Accessibility compliance for the HTML of this chapter is currently unknown and may be updated in the future.

Save book to Kindle

To save this book to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×