
By Gary F. Marcus
An try and combine theories approximately how the brain works, one who says that the brain is a computer-like manipulator of symbols, and one other that claims that the brain is a big community of neurons operating jointly in parallel.
Read Online or Download Algebraic Mind: Integrating Connectionism and Cognitive Science PDF
Similar educational psychology books
Overcoming Student Failure: Changing Motives and Incentives for Learning
Designed to be inspiring in addition to useful, the ''Psychology within the Classroom'' sequence has a couple of trouble-free gains to make the books effortless to evolve for school room use. Overcoming pupil Failure beneficial properties lecture room thoughts to offer scholars an incentive to benefit.
This booklet offers the history to investigate that used to be performed utilizing the Peer family review Questionnaire (PRAQ) for the Criminology examine Council (Australia). The ensuing qualitative and quantitative information is supplied on how colleges in Australia have handled bullying. The ebook additionally describes the categorical guidelines, plans, and actions that faculties were capable of strategically enforce to counter bullying.
Learning discourse : discursive approaches to research in mathematics education
The authors of this quantity declare that arithmetic could be usefully re-conceptualized as a distinct type of conversation. hence, the conventional dialogue of psychological schemes, misconceptions, and cognitive clash is reworked right into a attention of task, styles of interplay, and communique failure.
Adult Learning and Development: Perspectives From Educational Psychology
Grownup schooling happens each time members have interaction in sustained, systematic studying so as to have an effect on adjustments of their attitudes, wisdom, abilities, or trust platforms. studying, guideline, and developmental approaches are the first foci of academic psychology study and theorizing, yet academic psychologists' paintings in those domain names has based totally on the early life and adolescent tuition years.
- THE ART OF CHANGING THE BRAIN (HB)
- Psychology, 5th Edition
- Evidence-Based School Mental Health Services: Affect Education, Emotion Regulation Training, and Cognitive Behavioral Therapy
- Ethnicity, Race, and Nationality in Education: A Global Perspective (The Rutgers Invitational Symposium on Education Series)
- Race, Masculinity and Schooling (Educating Boys, Learning Gender)
- Cognitive Load Theory
Extra info for Algebraic Mind: Integrating Connectionism and Cognitive Science
Example text
For example, people have talked about Elman’s sentence-prediction model as if it had context-dependent representations of its input words. But in fact, the input nodes are context-independent (the word cat always turns on the same node regardless of where in a sentence it appears), and the hidden nodes do not truly represent individual words; instead, the hidden units represent sentence fragments. So it’s not that cat is represented differently by the hidden units in the sentence cats chase mice as opposed to the sentence I love cats.
But it is possible to have an input variable that is represented by a single node that takes on discrete values or by a set of nodes that take on continuous activation values. What is important for present purposes is not whether a node is analog or binary but rather whether a given variable is represented by a single node or many. 1 Models That Allocate One Node to Each Variable With this distinction—between representational schemes that allocate one node per variable and representational schemes that allocate more than one node per variable—firmly in mind (and clearly distinguished from the separate question of localist versus distributed encoding), we are now ready to consider the relation between multilayer perceptrons and systems that represent and generalize operations over variables.
Put informally, the network has no way to tell that all four columns should be treated uniformly. People may not always treat the columns uniformly, but certainly under some conditions they can, and these conditions pose difficulties for the many-nodes-per-variable models that are trained by the back-propagation learning algorithm. Relations between Variables 47 Training independence A bit more formally, we can say that manynodes-per-variable multilayer perceptrons that are trained by backpropagation cannot generalize one-to-one mappings between nodes.