Cooperative group problem solving and decision making may be conceptualized as a social combination process that maps a distribution of individual preferences into a single collective decision. As a test of a hypothesized truth-supported wins process, in which two correct group members are necessary and sufficient for a correct group response, 318 college students responded to 30 verbal analogy items as individuals. They next re-took the same analogies as a six-person cooperative group or as control individuals, and then a third time as individuals. Both a model-fitting and a model-testing approach indicated the hypothesized truth-supported wins social combination process. Groups performed considerably better than individuals on the second test. There was considerable individual learning during the group interaction, as indicated by a probability of .80 of a correct third-test individual response for members of correct groups who had initially been incorrect as individuals in contrast to a probability of .36 for members of incorrect groups who had initially been correct as individuals.Cooperative group problem solving and decision making may be conceptualized as a social combination process that maps a distribution of individual preferences into a single collective decision (e.g.,
This research assessed the relative impact of habit and behavioral intentions in predicting classroom teacher behavior, using a model proposed by Triandis. Responses from a behavioral differential, as well as two hours of classroom observations, were taken on 77 male and female black and white junior high school teachers. The classroom observation technique (STOIC) obtained the frequencies of emitted behaviors (both verbal and nonverbal), categorized by race and sex of the target child. Results indicated that habit was a more potent predictor of classroom behavior than intentions. However, a post-hoc analysis supported the notion that intentions become important when the habit component can be suppressed.
The popular problem-solving game of Mastermind may be considered a complex concept-learning problem with a selection paradigm and an unusual set of feedback rules. Analysis of the game tree for a simplified version of Mastermind suggested two selection strategies-focusing and tactical-analogous to those identified in previous research on other concept-learning problems. It was predicted that performance would be better for subjects who used these two strategies than for those who did not. This prediction was supported in two experiments, both for subjects who freely chose the two strategies and for those who were induced to use the two strategies. We propose that Mastermind is an interesting and useful addition to standard tasks for concept-learning research.
Considering an interactive computer as a social stimulus suggests that contemporary social psychological theories can contribute to the prediction of user attitude and performance. In order to assist in the systematic exploration of this possibility, we developed DIALOGUE, an on-line system to investigate the effects of varying the computer's responses to the user. This system involves a presentation program that displays the computer's responses, performs the pacing of video information, and collects a variety of measurements, including the user's response time and the number of correct/incorrect user responses. DIALOGUE also includes a data manager that allows the experimenter to examine or modify the information collected by the presentation program. Utilizing DIALOGUE, we conducted a preliminary investigation of one aspect of human-computer interaction, the effects of varying the degree of human-like responses exhibited by the computer. Results suggest that (1) there are underlying dimensions of judgment involving perception of interactive computers, (2) a manipulation of human-like computer responses is reflected primarily in certain of these dimensions, and (3) such a manipulation influences user performance and feelings of responsibility. Factors related to the implementation of DIALOGUE are considered, and its potential for investigations of a variety of human-computer interactions is discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.