Comparing the effects of generating questions,testing, and restudying on students' long-term recall in university learning

We compared the long-term effects of generating questions by learners with answering questions (i.e., testing) and restudying in the context of a university lecture. In contrast to previous studies, students were not prepared for the learning strategies, learning content was experimentally controlled, and effects on factual and transfer knowledge were examined. Students' overall recall performance after one week profited from generating questions and testing but not from restudying. When analyzing the effects on both knowledge types separately, traditional analyses revealed that only factual knowledge appeared to benefit from testing. However, additional Bayesian analyses suggested that generating questions and testing similarly benefit factual and transfer knowledge compared with restudying. The generation of questions thus seems to be another powerful learning strategy, yielding similar effects as testing on long-term retention of coherent learning content in educational contexts, and these effects emerge for factual and transfer knowledge.     

Dynamics properties of knowledge acquisition

Repeated counteraction of current knowledge and reality observation generates new knowledge and can be viewed as a dynamic process. When observed objects are not results of human activity, the dynamics results in acquisition of new knowledge, usually as a refinement of the existing one. Otherwise, adjustment between incomplete knowledge and reality can be a result of intentional modification of objects in question, as it happens in design of any artifact. In this case convergence of the process is questionable, for example, it may imply the end of the technical progress. In worst case scenario, the same computable criteria used simultaneously to modify objects and evaluate the result quality causing drift from an established goal and devaluation of acquired knowledge.     

Notes on attribution functions

Let be the knowledge space derived from an attribution function σ on Q. Under an assumption for σ, this paper gives some necessary and sufficient conditions such that is discriminative. It also discusses the resolubility of σ when Q is an infinite set. More precisely, this paper proves that σ is not resoluble if Q is uncountable, and gives a necessary and sufficient condition such that σ is resoluble when is -well-graded. By way of applications of these results, discriminativeness and resolubility are discussed around the merge of skill multimaps and the meshing of the delineated knowledge spaces.     

Human stigmergy: Theoretical developments and new applications

This paper contextualizes and introduces this special issue.     

Approximately counting and sampling knowledge states

Approximately counting and sampling knowledge states from a knowledge space is a problem that is of interest for both applied and theoretical reasons. However, many knowledge spaces used in practice are far too large for standard statistical counting and estimation techniques to be useful. Thus, in this work we use an alternative technique for counting and sampling knowledge states from a knowledge space. This technique is based on a procedure variously known as subset simulation, the Holmes–Diaconis–Ross method, or multilevel splitting. We make extensive use of Markov chain Monte Carlo methods and, in particular, Gibbs sampling, and we analyse and test the accuracy of our results in numerical experiments.     

The role of behavioral mind‐sets in goal‐directed activity: Conceptual underpinnings and empirical evidence

The cognitive and motor behavior that people perform in the course of pursuing a goal can induce a mind-set that persists to influence the strategy they use to attain very different goals in unrelated situations. Although the strategies governed by a mind-set are typically applied consciously and deliberately, they are performed without awareness of the reasons for their selection. Research in both social psychology and consumer behavior exemplifies the impact of mind-sets on comprehension, judgments, and decision making, thus providing evidence of the scope and diversity of their effects.     

The role of idiosyncratic attribute evaluation in mass customization

The growing use of mass customization necessitates an understanding of consumers' evaluations of mass customization platforms. We hypothesize that consumers' objective and subjective knowledge of the customized product moderate the influence of idiosyncratically evaluated (i.e., personalizable) attributes on satisfaction with a customization platform. Consistent with our theoretical framework, results from three experiments show that offering greater variety in idiosyncratically evaluated attribute options increases consumers' satisfaction to a greater extent for: (1) novices than experts (2) consumers with more subjective knowledge, and (3) miscalibrated consumers whose subjective knowledge does not match their objective knowledge, than calibrated consumers whose subjective and objective knowledge match.