G*Power (Erdfelder, Faul, & Buchner, 1996) was designed as a general stand-alone power analysis program for statistical tests commonly used in social and behavioral research. G*Power 3 is a major extension of, and improvement over, the previous versions. It runs on widely used computer platforms (i.e., Windows XP, Windows Vista, and Mac OS X 10.4) and covers many different statistical tests of thet, F, and χ2 test families. In addition, it includes power analyses forz tests and some exact tests. G*Power 3 provides improved effect size calculators and graphic options, supports both distribution-based and design-based input modes, and offers all types of power analyses in which users might be interested. Like its predecessors, G*Power 3 is free.

https://link.springer.com/content/pdf/10.3758/BF03193146.pdf

G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences

Recent studies of eye movements in reading and other information processing tasks, such as music reading, typing, visual search, and scene perception, are reviewed. The major emphasis of the review is on reading as a specific example of cognitive processing. Basic topics discussed with respect to reading are (a) the characteristics of eye movements, (b) the perceptual span, (c) integration of information across saccades, (d) eye movement control, and (e) individual differences (including dyslexia). Similar topics are discussed with respect to the other tasks examined. The basic theme of the review is that eye movement data reflect moment-to-moment cognitive processes in the various tasks examined. Theoretical and practical considerations concerning the use of eye movement data are also discussed.

/pdf/eye-movements-in-reading-and-information-processing-20-years-3z5ay8hdwc.pdf

Eye movements in reading and information processing: 20 years of research.

Running head: WHY MINIMALLY GUIDED INSTRUCTION DOES NOT WORK Why Minimal Guidance during Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching

Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert–novice differences, and cognitive load. Although unguided or minimally guided instructional approaches are very popular and intuitively appealing, the point is made that these approaches ignore both the structures that constitute human cognitive architecture and evidence from empirical studies over the past half-century that consistently indicate that minimally guided instruction is less effective and less efficient than instructional approaches that place a strong emphasis on guidance of the student learning process. The advantage of guidance begins to recede only when learners have sufficiently high prior knowledge to provide "internal" guidance. Recent developments in instructional research and instructional design models that support guidance during instruction are briefly described.

/pdf/why-minimal-guidance-during-instruction-does-not-work-an-3q3gc2rbj6.pdf

Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching

From the Publisher:
The old opposition of matter versus mind stubbornly persists in the way we study mind and brain. In treating cognition as problem solving, Andy Clark suggests, we may often abstract too far from the very body and world in which our brains evolved to guide us. Whereas the mental has been treated as a realm that is distinct from the body and the world, Clark forcefully attests that a key to understanding brains is to see them as controllers of embodied activity. From this paradigm shift he advances the construction of a cognitive science of the embodied mind.

/pdf/being-there-putting-brain-body-and-world-together-again-31tt4y51ml.pdf

Being There: Putting Brain, Body, and World Together Again

Two experiments that tested the hypothesis that the effect of stimulus presentation prob­ ability on perceptual processing is a function of the preceding stimulus sequence are reported. Replicating previous findings, the magnitude of the probability effect was affected by stimulus quality. The interaction was unchanged when sequential effects were eliminated from the data. Stimulus quality and sequence displayed an additive relationship. These results suggest that the probability effect on perceptual processing is not an indirect result of sequential effects. Together with the results of Miller and Anbar (1981), they suggest that practice gradually acts to facilitate the perceptual processing of highly probable stimuli.

/pdf/the-effects-of-stimulus-sequence-and-probability-on-4urndcnrac.pdf

The effects of stimulus sequence and probability on perceptual processing.

In probabilistic categorization tasks, the correct category is determined only probabilistically by the stimulus pattern Data from such experiments have been successfully accounted for by a simple network model, but have posed difficulties for exemplar models In the present article, we consider an exemplar model, CLEM (concept learning by exemplar memorization), which differs from previously tested exemplar models in that exemplar traces are assumed to be stored only when the subject has guessed or made a classification error Fits of CLEM to both learning and test data were comparable to those of the network model, and better than those obtained for a version of CLEM in which encoding was independent of the subject's response The implications of these results for the processes underlying classification decisions are discussed

Modeling Probabilistic Categorization Data: Exemplar Memory and Connectionist Nets

Ss were required to judge whether pairs of letters were identical with respect to name (Experiment 1) or form (Experiment 2). The results replicated the findings of Posner & Mitchell (1967) that physically identical letters could be matched more quickly than those only sharing the same name. When members of a letter pair differed in color, Ss showed a small but reliable tendency to respond more slowly when making “same” judgments, even when the letters only shared the same name. “Different” judgments were unaffected by color differences. To account for the effects of color variation, it seems necessary to consider both distraction and response competition factors.

/pdf/effects-of-color-differences-in-a-letter-matching-task-r4snp17rle.pdf

Effects of color differences in a letter matching task

/pdf/treatment-implications-and-possible-mechanisms-1kzyp6dgnm.pdf

Arnold D. Well

Papers

The effects of stimulus sequence and probability on perceptual processing.

Modeling Probabilistic Categorization Data: Exemplar Memory and Connectionist Nets

Effects of color differences in a letter matching task

Treatment Implications and Possible Mechanisms

Hale and Stevenson's failure to find a developmental trend in the effects of distraction: A floor effect