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Say What? Automatic Modeling of Collaborative Problem Solving Skills from Student Speech in the Wild
Pugh, Samuel L.; Subburaj, Shree Krishna; Rao, Arjun Ramesh; Stewart, Angela E. B.; Andrews-Todd, Jessica; D'Mello, Sidney K. – International Educational Data Mining Society, 2021
We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…
Descriptors: Problem Solving, Cooperation, Middle School Students, High School Students
Shafat, Gabriel; Levin, Ilya – International Association for Development of the Information Society, 2012
This paper deals with two types of logical problems--recognition problems and reverse engineering problems, and with the interrelations between these types of problems. The recognition problems are modeled in the form of a visual representation of various objects in a common pattern, with a composition of represented objects in the pattern.…
Descriptors: Foreign Countries, Information Seeking, Online Searching, Search Strategies
Cocking, Rodney R. – 1980
The relative importance of spatial-position as a memory aid in a block pattern reproduction task was investigated by analyzing the object-selection and object-placement strategies of 69 nursery school children. Subjects were given a task modeled on Piaget's assessment of Static Reproductive Images and Action that had been modified into a…
Descriptors: Cognitive Processes, Cues, Memory, Pattern Recognition
Hayes-Roth, Frederick – 1980
This paper discusses the theoretical problem of matching and abstraction of concepts as the processes occur in human minds, and the structures used to represent these processes for use in automated, knowledge based systems. A basic premise of the paper is that hierarchies play a crucial role in structuring knowledge and in solving problems. Data…
Descriptors: Abstract Reasoning, Artificial Intelligence, Automation, Databases
Snyder, Robin M. – 1996
Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Computer System Design, Expert Systems
Swanson, Lee – 1978
This study compared the conceptual rule learning performance of normal and learning disabled children. Subjects for the study were 18 normal and 18 learning disabled children with mean ages of 9.4 and 9.3 years and mean IQ scores of 103.1 and 101.6 respectively. The children were matched for age, IQ, sex and race. Four types of rules (affirmation,…
Descriptors: Classification, Concept Formation, Difficulty Level, Elementary School Students

Hirsch, Christian R., Ed.; And Others – Mathematics Teacher, 1987
Activities to extend the core curriculum through the study of the periodicity of rational numbers to help students develop calculator and research skills are presented. Four worksheets are included, to be used as discovery activities. A computer program is listed, as well as examples of periodic pictures. (MNS)
Descriptors: Calculators, Computer Software, Discovery Learning, Instructional Materials
Harrison, Algea Othello – 1975
Aspects of problem-solving measured here are delay of gratification, field-dependence independence, and the relection-impulsivity dimension. The following hypotheses are proposed (1) Those subjects who score high on externality will not delay gratification as those who score low, but they will score lower on measures on field-independence than…
Descriptors: Academic Achievement, Black Youth, Decision Making, Decision Making Skills