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Intelligent or merely literate?
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TRENDS in Cognitive Sciences Vol.5 No.2 February 2001
89
Book review
A bird’s eye view of cognition The Alex Studies: Cognitive and Communicative Abilities of Grey Parrots by I.M. Pepperberg, Harvard University Press, 2000. £24.95 (434 pages) ISBN 0 674 00051 X
Chapter 1 of the Kama Sutra suggests that in order to live a healthy, aesthetically pleasing life, one should spend at least one hour every morning teaching parrots to speak. In contrast to most unrefined cognitive scientists, Irene Pepperberg has taken this maxim to heart. Since 1977, she and her colleagues at the University of Arizona have spent nearly ten hours a day teaching parrots – or more specifically, one African grey parrot, Alex – to speak. The culmination of her 23 years of aesthetic living is The Alex Studies: Cognitive and Communicative Abilities of Grey Parrots. The Alex Studies reads as a historical account of Pepperberg’s work with Alex, beginning with the day that Alex was plucked at random from among his pet store cagemates to become part of scientific history. As we read in Chapter 2, Pepperberg attributes Alex’s success not to a lucky choice on the part of the pet store staff, but to the use of a novel training paradigm which she calls the Model/Rival (M/R) technique. In this training paradigm, the subject watches as two human experimenters interact in a way that imitates the type of responses that the subject is meant to learn. Thus, one of the experimenters asks the other a question about an object (e.g. ‘what color?’). If the learner answers correctly, she is praised and receives the object as a reward. If she answers incorrectly or unclearly, the teacher removes the object and scolds her. In this way, the other experimenter serves both as the model for Alex’s behavior and as his rival for the experimenter’s attention. Alex, who wants access to the objects and the experimenters, soon gets in on the action, mimicking the labels used by the experimenter and the training begins. Once trained on new labels and concepts using the M/R technique, Alex is then tested in a series of novel generalization tasks. http://tics.trends.com
The chapters that follow demonstrate the success of the M/R technique and the remarkable degree of Alex’s cognitive abilities. At present, Alex can produce and comprehend over 50 words, including words for colors, materials and shapes. He can make simple requests (e.g. ‘want cork’). He is able to count up to six. He passes standard tests of object permanence and understands relative concepts like same/different and bigger/smaller. Each chapter describes Alex’s training and testing in painstaking detail and provides numerous examples that go beyond the statistics and give the reader a true sense of Alex’s mastery of different tasks. Throughout, Pepperberg is careful to tackle alternative explanations and cautious about her interpretations of Alex’s performance. Although Alex’s capacities will undoubtedly impress even the most skeptical of readers, those well-versed in the cognitive sciences may be left somewhat dissatisfied with Pepperberg’s discussion of Alex’s accomplishments. For although she often compares Alex’s performance to that of other animals, especially languagetrained primates and marine mammals, she rarely applies Alex’s performance to unanswered questions in the fields of human cognition and development. In Chapter 7, for example, Pepperberg examines whether Alex can understand and use numerical concepts. Although she ties his striking performance to the literature on subitizing abilities in animals, she fails to relate Alex’s numerical abilities to the current debate about number representation in non-human animals and prelinguistic infants1,2. Similarly, Alex’s impressive ability to learn words is all too rarely linked up with work on children’s word learning. As we learn in Chapter 4, Alex seemed to master his first color terms quite easily, but human children struggle to learn their first color labels3. Why does Alex learn color words so easily? Does his representation of color concepts differ from those of young children? In short, although Pepperberg continuously gives the reader a great appreciation of Alex’s striking performance, she rarely provides us with much insight into the representations underlying this performance. Pepperberg intends her work to be a ‘panoramic view of [the] data’ (p. ix),and it is certainly that and even more. Although her cautious intepretations may frustrate
those cognitive scientists interested in her take on the nature of avian conceptual representations, The Alex Studies is a rich and well-organized summary of all the work with Alex to date and provides an indispensable reference for anyone interested in her research program. References 1 Hauser, M.D. and Carey, S. (1998) Building a cognitive creature from a set of primitives: evolutionary and developmental insights. In The Evolution of Mind (Cummins, D. and Allen C., eds), pp. 51–106, Oxford University Press 2 Wynn, K. (1998) Psychological foundations of number: numerical competence in human infants. Trends Cognit. Sci. 2, 296–303 3 Sandhofer, C.M. and Smith, L.B. (1999) Learning color words involves learning a system of mappings. Dev. Psychol. 35, 668–679
Laurie R. Santos Dept of Psychology, Harvard University, Cambridge, MA 02138, USA e-mail: [email protected]
Intelligent or merely literate? Changing Minds: Computers, Learning and Literacy Andrea A. diSessa, MIT Press, 2000. £20.50 / $29.95 ISBN 0 262 04180 4
The advent of new technologies in educational settings has provided a fertile area of research for psychologists, offering opportunities to test and evaluate a range of learning theories that examine issues in human computer interaction and investigate the dynamics of effective group work. The work of diSessa and colleagues at the MIT Technology into Education Group is at the forefront of much of this research. The upbeat title of Changing Minds: Computers, Learning and Literacy is exactly what one would expect from the MIT group. diSessa does not focus on the mundane subject of technology as an efficient deliverer of knowledge or an electronic resource. Instead, making sense of the interplay between users and technology is the key. At the outset diSessa gently diffuses three recurring issues surrounding the
90
Forum
impact of educational technology – those of the poverty of the resource base, acceptable pedagogies and demonstrable outcomes. There is no shortage of resources in our schools, simply a shortage of effective use of computers. Although, according to diSessa, ‘make it experiential’ is the most powerful of all educational heuristics, he makes no claim that this is the only pedagogic approach. Thus, he allows that more-prosaic teaching and learning experiences also have their place. When he asks the rhetorical question, ‘Do computers convey to humans a new increment of intellectual power equivalent to conventional literacy? ’ he finds himself at odds with the techno-sceptics who insist that there is no evidence of positive, and some evidence of negative, outcomes of educational computer use. diSessa agrees that there is poor use of technology, hence negative impacts, but argues ‘good usage’ requires radical shifts in the nature of the education process. Technology in the wrong place for the wrong reason necessarily proves ineffective but this is no reason to reject such a powerful mind-tool. Having swept these three contentious issues from the board, diSessa presents his main thesis: the importance of computational literacy. However, he rapidly rejects the term literacy as too fuzzy, opting instead for the term material intelligence. This is the level of intelligence we can achieve when materials – signs, symbols and tools such as calculus, algebra, an abacus or a computer – are used to enhance, empower or indeed shape mental intelligence (cognition). This echoes the description of Salomon et al.1 of effects of and effects with technology. The former being the residues left behind when the engagement is complete (changing minds), whereas the latter are the empowerment the technology affords while engaged with the technology (the tyre-lever principle). The development of material intelligence is further mediated by the availability of relevant social niches. Tools can be ‘fit-forpurpose’ but if they are not accepted by a society and if they do not find a social niche, they will have little impact on the development of new understandings. Moving on from his key idea, diSessa starts his defence of educational technology with a series of historical vignettes showing how new representational tools allowed major new understandings to emerge. Newton and Leibniz’s development of calculus are powerful examples of such http://tics.trends.com
TRENDS in Cognitive Sciences Vol.5 No.2 February 2001
advances. He goes on to show that ‘average high-school children’ using BOXER (a software tool that allows the learner to build, adapt and test mathematical and scientific ideas), can emulate Galileo’s ground breaking work and deduce his laws of motion. New tools bring solutions to problems, once the province of the exceptional few, within the scope of the average. His argument is that computational representations, such as those that can be developed using BOXER, change the landscape of learning. These enrichment frameworks challenge our conceptions of what is to be learnt, how we learn it and of course, requires us to refine our concept of what a ‘learning gain’ means. This is a crucial, if not new, debate. If our educational system continues to be driven by traditional goals then it will be increasingly out of step with activities in the work place and, indeed, in the informal learning situations that are now developing with the use of network technologies. diSessa’s excitement and belief in the effectiveness of such tools are tempered by his very real understanding of educational change. He points out that schools are impoverished tool creators and users, with a major barrier being the poor effort-tooutput ratio of learning to use many computer tools. He argues, as we have also done2, that we must build tools that are functional, adaptive and readily usable by both teachers and students. The effort-tooutcome ratio must be improved or software will not achieve that all-important social acceptance by the educational community. Finally, diSessa states that his book is not an easy read but I beg to differ. He not only signposts the main arguments in his preface but he also provides adequate indices and notes to further help the reader. In spite of presenting a grand sweep of the field this text is realistic as well as thought provoking. As such this is a ‘must have’ book for anyone working in the field of educational technology. References 1 Salomon, G. et al. (1991) Partners in cognition: extending human intelligence with intelligent technologies. Educ. Research 20, 2–9 2 Wood, D. et al. (1999) Integrated learning systems in the classroom. Comput. Educ. 33, 91–108
Jean Underwood Division of Psychology, The Nottingham Trent University, Burton Street, Nottingham, UK NG1 4BU e-mail: [email protected]
Of rabbits and children How Children Learn the Meanings of Words by Paul Bloom, MIT Press, 2000. $39.95 (xii + 300 pages) ISBN 0 262 02469 1
This enjoyable book concerns the nature and development of the human mind. More specifically, the book addresses the challenge facing young children when learning the meanings of words. At first glance, one might wonder where the problem lies. After all, the majority of children have broken the language barrier and become expert word learners before they can tie their shoes. Upon closer examination, however, it becomes clear that the ability to learn and use words is not a trivial task. Take the famous philosophical conundrum introduced by Quine1 that involves a linguist visiting a foreign land and hearing a native use the word ‘gavagai’as a rabbit runs by. Quine argues that there is an infinite number of possible word-to-world mappings in this situation. Here, in his first chapter, Bloom points out that there are at least three problems facing the young word learner. The first problem is how the child knows that ‘gavagai’ is a word – or how to solve the ‘segmentation problem’. The second problem is the ‘reference problem’ – how the child knows what the word is referring to; is it the rabbit as a whole, the rabbit’s ears, the rabbit’s motion, etc? The third and final problem is for the word learner to figure out how to extend this word appropriately; that is, the ‘generalization problem’. Paul Bloom promises to tell us ‘everything I know about how children learn the meanings of words’. He keeps his promise in 11 chapters that survey all the critical findings and theories on lexical development over the past 20 years. Of course, he also lays out his own conceptual model, which proposes that word learning is accomplished through domain-general processes and without the support of special biases or modules. The reader not cognizant of the research in this area will need to know what is original about this view and whether there is empirical evidence to support it. In a nutshell, Bloom argues that the acquisition of word meaning requires an ability to infer the intentions of others, an ability to acquire
TRENDS in Cognitive Sciences Vol.5 No.2 February 2001
89
Book review
A bird’s eye view of cognition The Alex Studies: Cognitive and Communicative Abilities of Grey Parrots by I.M. Pepperberg, Harvard University Press, 2000. £24.95 (434 pages) ISBN 0 674 00051 X
Chapter 1 of the Kama Sutra suggests that in order to live a healthy, aesthetically pleasing life, one should spend at least one hour every morning teaching parrots to speak. In contrast to most unrefined cognitive scientists, Irene Pepperberg has taken this maxim to heart. Since 1977, she and her colleagues at the University of Arizona have spent nearly ten hours a day teaching parrots – or more specifically, one African grey parrot, Alex – to speak. The culmination of her 23 years of aesthetic living is The Alex Studies: Cognitive and Communicative Abilities of Grey Parrots. The Alex Studies reads as a historical account of Pepperberg’s work with Alex, beginning with the day that Alex was plucked at random from among his pet store cagemates to become part of scientific history. As we read in Chapter 2, Pepperberg attributes Alex’s success not to a lucky choice on the part of the pet store staff, but to the use of a novel training paradigm which she calls the Model/Rival (M/R) technique. In this training paradigm, the subject watches as two human experimenters interact in a way that imitates the type of responses that the subject is meant to learn. Thus, one of the experimenters asks the other a question about an object (e.g. ‘what color?’). If the learner answers correctly, she is praised and receives the object as a reward. If she answers incorrectly or unclearly, the teacher removes the object and scolds her. In this way, the other experimenter serves both as the model for Alex’s behavior and as his rival for the experimenter’s attention. Alex, who wants access to the objects and the experimenters, soon gets in on the action, mimicking the labels used by the experimenter and the training begins. Once trained on new labels and concepts using the M/R technique, Alex is then tested in a series of novel generalization tasks. http://tics.trends.com
The chapters that follow demonstrate the success of the M/R technique and the remarkable degree of Alex’s cognitive abilities. At present, Alex can produce and comprehend over 50 words, including words for colors, materials and shapes. He can make simple requests (e.g. ‘want cork’). He is able to count up to six. He passes standard tests of object permanence and understands relative concepts like same/different and bigger/smaller. Each chapter describes Alex’s training and testing in painstaking detail and provides numerous examples that go beyond the statistics and give the reader a true sense of Alex’s mastery of different tasks. Throughout, Pepperberg is careful to tackle alternative explanations and cautious about her interpretations of Alex’s performance. Although Alex’s capacities will undoubtedly impress even the most skeptical of readers, those well-versed in the cognitive sciences may be left somewhat dissatisfied with Pepperberg’s discussion of Alex’s accomplishments. For although she often compares Alex’s performance to that of other animals, especially languagetrained primates and marine mammals, she rarely applies Alex’s performance to unanswered questions in the fields of human cognition and development. In Chapter 7, for example, Pepperberg examines whether Alex can understand and use numerical concepts. Although she ties his striking performance to the literature on subitizing abilities in animals, she fails to relate Alex’s numerical abilities to the current debate about number representation in non-human animals and prelinguistic infants1,2. Similarly, Alex’s impressive ability to learn words is all too rarely linked up with work on children’s word learning. As we learn in Chapter 4, Alex seemed to master his first color terms quite easily, but human children struggle to learn their first color labels3. Why does Alex learn color words so easily? Does his representation of color concepts differ from those of young children? In short, although Pepperberg continuously gives the reader a great appreciation of Alex’s striking performance, she rarely provides us with much insight into the representations underlying this performance. Pepperberg intends her work to be a ‘panoramic view of [the] data’ (p. ix),and it is certainly that and even more. Although her cautious intepretations may frustrate
those cognitive scientists interested in her take on the nature of avian conceptual representations, The Alex Studies is a rich and well-organized summary of all the work with Alex to date and provides an indispensable reference for anyone interested in her research program. References 1 Hauser, M.D. and Carey, S. (1998) Building a cognitive creature from a set of primitives: evolutionary and developmental insights. In The Evolution of Mind (Cummins, D. and Allen C., eds), pp. 51–106, Oxford University Press 2 Wynn, K. (1998) Psychological foundations of number: numerical competence in human infants. Trends Cognit. Sci. 2, 296–303 3 Sandhofer, C.M. and Smith, L.B. (1999) Learning color words involves learning a system of mappings. Dev. Psychol. 35, 668–679
Laurie R. Santos Dept of Psychology, Harvard University, Cambridge, MA 02138, USA e-mail: [email protected]
Intelligent or merely literate? Changing Minds: Computers, Learning and Literacy Andrea A. diSessa, MIT Press, 2000. £20.50 / $29.95 ISBN 0 262 04180 4
The advent of new technologies in educational settings has provided a fertile area of research for psychologists, offering opportunities to test and evaluate a range of learning theories that examine issues in human computer interaction and investigate the dynamics of effective group work. The work of diSessa and colleagues at the MIT Technology into Education Group is at the forefront of much of this research. The upbeat title of Changing Minds: Computers, Learning and Literacy is exactly what one would expect from the MIT group. diSessa does not focus on the mundane subject of technology as an efficient deliverer of knowledge or an electronic resource. Instead, making sense of the interplay between users and technology is the key. At the outset diSessa gently diffuses three recurring issues surrounding the
90
Forum
impact of educational technology – those of the poverty of the resource base, acceptable pedagogies and demonstrable outcomes. There is no shortage of resources in our schools, simply a shortage of effective use of computers. Although, according to diSessa, ‘make it experiential’ is the most powerful of all educational heuristics, he makes no claim that this is the only pedagogic approach. Thus, he allows that more-prosaic teaching and learning experiences also have their place. When he asks the rhetorical question, ‘Do computers convey to humans a new increment of intellectual power equivalent to conventional literacy? ’ he finds himself at odds with the techno-sceptics who insist that there is no evidence of positive, and some evidence of negative, outcomes of educational computer use. diSessa agrees that there is poor use of technology, hence negative impacts, but argues ‘good usage’ requires radical shifts in the nature of the education process. Technology in the wrong place for the wrong reason necessarily proves ineffective but this is no reason to reject such a powerful mind-tool. Having swept these three contentious issues from the board, diSessa presents his main thesis: the importance of computational literacy. However, he rapidly rejects the term literacy as too fuzzy, opting instead for the term material intelligence. This is the level of intelligence we can achieve when materials – signs, symbols and tools such as calculus, algebra, an abacus or a computer – are used to enhance, empower or indeed shape mental intelligence (cognition). This echoes the description of Salomon et al.1 of effects of and effects with technology. The former being the residues left behind when the engagement is complete (changing minds), whereas the latter are the empowerment the technology affords while engaged with the technology (the tyre-lever principle). The development of material intelligence is further mediated by the availability of relevant social niches. Tools can be ‘fit-forpurpose’ but if they are not accepted by a society and if they do not find a social niche, they will have little impact on the development of new understandings. Moving on from his key idea, diSessa starts his defence of educational technology with a series of historical vignettes showing how new representational tools allowed major new understandings to emerge. Newton and Leibniz’s development of calculus are powerful examples of such http://tics.trends.com
TRENDS in Cognitive Sciences Vol.5 No.2 February 2001
advances. He goes on to show that ‘average high-school children’ using BOXER (a software tool that allows the learner to build, adapt and test mathematical and scientific ideas), can emulate Galileo’s ground breaking work and deduce his laws of motion. New tools bring solutions to problems, once the province of the exceptional few, within the scope of the average. His argument is that computational representations, such as those that can be developed using BOXER, change the landscape of learning. These enrichment frameworks challenge our conceptions of what is to be learnt, how we learn it and of course, requires us to refine our concept of what a ‘learning gain’ means. This is a crucial, if not new, debate. If our educational system continues to be driven by traditional goals then it will be increasingly out of step with activities in the work place and, indeed, in the informal learning situations that are now developing with the use of network technologies. diSessa’s excitement and belief in the effectiveness of such tools are tempered by his very real understanding of educational change. He points out that schools are impoverished tool creators and users, with a major barrier being the poor effort-tooutput ratio of learning to use many computer tools. He argues, as we have also done2, that we must build tools that are functional, adaptive and readily usable by both teachers and students. The effort-tooutcome ratio must be improved or software will not achieve that all-important social acceptance by the educational community. Finally, diSessa states that his book is not an easy read but I beg to differ. He not only signposts the main arguments in his preface but he also provides adequate indices and notes to further help the reader. In spite of presenting a grand sweep of the field this text is realistic as well as thought provoking. As such this is a ‘must have’ book for anyone working in the field of educational technology. References 1 Salomon, G. et al. (1991) Partners in cognition: extending human intelligence with intelligent technologies. Educ. Research 20, 2–9 2 Wood, D. et al. (1999) Integrated learning systems in the classroom. Comput. Educ. 33, 91–108
Jean Underwood Division of Psychology, The Nottingham Trent University, Burton Street, Nottingham, UK NG1 4BU e-mail: [email protected]
Of rabbits and children How Children Learn the Meanings of Words by Paul Bloom, MIT Press, 2000. $39.95 (xii + 300 pages) ISBN 0 262 02469 1
This enjoyable book concerns the nature and development of the human mind. More specifically, the book addresses the challenge facing young children when learning the meanings of words. At first glance, one might wonder where the problem lies. After all, the majority of children have broken the language barrier and become expert word learners before they can tie their shoes. Upon closer examination, however, it becomes clear that the ability to learn and use words is not a trivial task. Take the famous philosophical conundrum introduced by Quine1 that involves a linguist visiting a foreign land and hearing a native use the word ‘gavagai’as a rabbit runs by. Quine argues that there is an infinite number of possible word-to-world mappings in this situation. Here, in his first chapter, Bloom points out that there are at least three problems facing the young word learner. The first problem is how the child knows that ‘gavagai’ is a word – or how to solve the ‘segmentation problem’. The second problem is the ‘reference problem’ – how the child knows what the word is referring to; is it the rabbit as a whole, the rabbit’s ears, the rabbit’s motion, etc? The third and final problem is for the word learner to figure out how to extend this word appropriately; that is, the ‘generalization problem’. Paul Bloom promises to tell us ‘everything I know about how children learn the meanings of words’. He keeps his promise in 11 chapters that survey all the critical findings and theories on lexical development over the past 20 years. Of course, he also lays out his own conceptual model, which proposes that word learning is accomplished through domain-general processes and without the support of special biases or modules. The reader not cognizant of the research in this area will need to know what is original about this view and whether there is empirical evidence to support it. In a nutshell, Bloom argues that the acquisition of word meaning requires an ability to infer the intentions of others, an ability to acquire