Literature Index

Displaying 2711 - 2720 of 3326
  • Author(s):
    delMas, R. C.
    Year:
    1988
    Abstract:
    The differential effect of two activity-based instructional treatments on subjects' concepts of probability was investigated.
    Location:
  • Author(s):
    Clark, M.
    Editors:
    Brunelli, L., & Cicchitelli, G.
    Year:
    1993
    Abstract:
    In 1993 a sample of 102 class members participated in an exploratory study which consisted of ten pairs of statistical questions. For each pair students were asked to specify which of the two options they felt that they would prefer to answer if they were required to or if they had no preference. They were also asked if they could say why they chose particular options. This study clearly indicated that in some ares the students had very definite preferences (70% or more of the group) for particular contexts over others.
  • Author(s):
    Luc Budé, Tjaart Imbos, Margaretha W. J. v. d. Wiel, Nick J. Broers and Martijn P. F. Berger
    Year:
    2009
    Abstract:
    In this study directive tutor guidance in problem-based learning (PBL) of statistics is investigated. In a quasi experiment in an educational setting, directive guiding tutors were compared with tutors in a more traditional role. Results showed that the subjective perceptions of the students with regard to the course, the tutor, and the discussions in the tutorial meetings were more positive in the guided condition. The quality of the problems used in the meetings and general tutor functioning were evaluated as equal in both conditions. Achievement was marginally higher in the guided condition. It can be concluded that directive tutor guidance is an effective addition to PBL of statistics.
  • Author(s):
    Sterling, J., & Gray, M. W.
    Year:
    1991
    Abstract:
    Although the use of software has become widespread in elementary statistics courses, there has been little formal evaluation of its effectiveness. In this experiment with the use of software, primarily for simulations in an introductory statistics course, effectiveness was measured in two ways: whether students did better on examinations and whether they believed that the software was useful. Results showed that students did significantly better on the examinations and that about half of them considered the software to be useful. However, even among those who believed that the software was helpful, many objected to the extra time involved.
  • Author(s):
    Kinga Morsanyi , Caterina Primi, Francesca Chiesi and Simon Handle
    Year:
    2009
    Abstract:
    In three studies we looked at two typical misconceptions of probability: the representativeness heuristic, and the equiprobability bias. The literature on statistics education predicts that some typical errors and biases (e.g., the equiprobability bias) increase with education, whereas others decrease. This is in contrast with reasoning theorists' prediction who propose that education reduces misconceptions in general. They also predict that students with higher cognitive ability and higher need for cognition are less susceptible to biases. In Experiments 1 and 2 we found that the equiprobability bias increased with statistics education, and it was negatively correlated with students' cognitive abilities. The representativeness heuristic was mostly unaffected by education, and it was also unrelated to cognitive abilities. In Experiment 3 we demonstrated through an instruction manipulation (by asking participants to think logically vs. rely on their intuitions) that the reason for these differences was that these biases originated in different cognitive processes.
  • Author(s):
    Hooper, S., et al.
    Year:
    1989
    Abstract:
    Discussion of the effects of group aptitudes on achievement during small group learning highlights two studies that examined the effects of group composition on high and low aptitude college students. Heterogeneous and homogeneous aptitude groups are described, and an individual mastery contingency in the second study is explained. (21 references) (LRW)
  • Author(s):
    Linda L. Cooper and Felice S. Shore
    Year:
    2010
    Abstract:
    Recognizing and interpreting variability in data lies at the heart of statistical reasoning. Since graphical displays should facilitate communication about data, statistical literacy should include an understanding of how variability in data can be gleaned from a graph. This paper identifies several types of graphs that students typically encounter-histograms, distribution bar graphs, and value bar charts. These graphs all share the superficial similarity of employing bars, and yet the methods to perceive variability in the data differ dramatically. We provide comparisons within each graph type for the purpose of developing insight into what variability means and how it is evident within the data's associated graph. We introduce graphical aids to visualize variability for histograms and value bar charts, which could easily be tied to numerical estimates of variability.
  • Author(s):
    Giraud, G., & Enders, C.
    Year:
    1998
    Abstract:
    This presentation reports the results of a study concerned with the issue of cooperative testing. Cooperative testing is defined as small group discussion of test items on the day of the exam and it's been proposed as a logical extension of cooperative learning. The results of the study showed that: (1) students' attitudes toward cooperative testing became more positive after each test administration, (2) self-reported study time varied among students, (3) students' perceptions of freeloading increased across test administrations, (4) the cooperative testing sections appeared to experience slightly less test anxiety than did the traditional testing section, and (5) testing condition did not appear to affect retention of course material.
  • Author(s):
    Galmacci, G. & Milito, A. M.
    Editors:
    Phillips, B.
    Year:
    2002
    Abstract:
    This paper describes the main results of a research project carried out in Italy at every school level to compare how different teaching approaches influence the students' learning process. The experiment involved more than 6000 pupils (age 6-19) at every school level and 338 teachers.
  • Author(s):
    Fong, G. T., Krantz, D. H., & Nisbett, R. E.
    Year:
    1986
    Abstract:
    People possess an abstract inferential rule system that is an intuitive version of the law of large numbers. Because the rule system is not tied to any particular content domain, it is possible to improve it by formal teaching techniques. We present four experiments that support this view. In Experiments 1 and 2, we taught subjects about the formal properties of the law of large numbers in brief training sessions in the laboratory and found that this increased both the frequency and the quality of statistical reasoning for a wide variety of problems of an everyday nature. In addition, we taught subjects about the rule by a "guided induction" technique, showing them how to use the rule to solve problems in particular domains. Learning from the examples was abstracted to such an extent that subjects showed just as much improvement on domains where the rule was not taught as on domains where it was. In Experiment 3, the ability to analyze an everyday problem with reference to the law of large numbers was shown to be much greater for those who had several years of training in statistics than for those who had less. Experiment 4 demonstrated that the beneficial effects of formal training in statistics may hold even when subjects are tested completely outside of the context of training. In general, these four experiments support a rather "formalist" theory of reasoning: People reason using very abstract rules, and their reasoning about a wide variety of content domains can be affects by direct manipulation of these abstract rules.

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