Providing Instruction Based on Students' Learning Style Preferences Does Not Improve Learning.

Teachers commonly categorize students as visual or auditory learners. Despite a lack of empirical evidence, teaching to a student's perceived learning style remains common practice in education (Pashler et al., 2009). Having conducted an extensive review of the literature, Pashler et al. (2009) noted, "...very few studies have even used an experimental methodology capable of testing the validity of learning styles applied to education" (p. 105). Rogowsky et al. (2015) published the first study following the experimental design prescribed by Pashler et al. Focusing specifically on the visual/auditory dichotomy, Rogowsky et al. (2015) examined the extent to which learning style predicts comprehension and retention based on mode of instruction. Their study has been noted as "The only study located through the systematic literature search across six different databases and the screening of more than 1000 records that was totally aligned with Pashler's criteria" (Aslaksen and Loras, 2018, p. 3). The caveat to the 2015 study is that it was conducted with adult learners. The current study uses the same design and methodology as its predecessor, but on a school-aged population, making it the first of its kind. Consistent with earlier findings with adults, results failed to find a significant relationship between auditory or visual learning style preference and comprehension. Fifth graders with a visual learning style scored higher than those with an auditory learning style on listening and reading comprehension measures. As such, and counter to current educational beliefs and practices, teachers may actually be doing a disservice to students by using resources to determine their learning style and then tailoring the curriculum to match that learning style.

Spectral integration plasticity in cat auditory cortex induced by perceptual training.

We investigated the ability of cats to discriminate differences between vowel-like spectra, assessed their discrimination ability over time, and compared spectral receptive fields in primary auditory cortex (AI) of trained and untrained cats. Animals were trained to discriminate changes in the spectral envelope of a broad-band harmonic complex in a 2-alternative forced choice procedure. The standard stimulus was an acoustic grating consisting of a harmonic complex with a sinusoidally modulated spectral envelope ("ripple spectrum"). The spacing of spectral peaks was conserved at 1, 2, or 2.66 peaks/octave. Animals were trained to detect differences in the frequency location of energy peaks, corresponding to changes in the spectral envelope phase. Average discrimination thresholds improved continuously during the course of the testing from phase-shifts of 96 degrees at the beginning to 44 degrees after 4-6 months of training with a 1 ripple/octave spectral envelope. Responses of AI single units and small groups of neurons to pure tones and ripple spectra were modified during perceptual discrimination training with vowel-like ripple stimuli. The transfer function for spectral envelope frequencies narrowed and the tuning for pure tones sharpened significantly in discriminant versus naïve animals. By contrast, control animals that used the ripple spectra only in a lateralization task showed broader ripple transfer functions and narrower pure-tone tuning than naïve animals.

Nonlinear modeling of auditory-nerve rate responses to wideband stimuli.

The spectral selectivity of auditory nerve fibers was characterized by a method based on responses to random-spectrum-shape stimuli. The method models the average discharge rate of fibers for steady stimuli and is based on responses to approximately 100 noise-like stimuli with pseudorandom spectral levels in 1/8- or 1/16-octave frequency bins. The model assumes that rate is determined by a linear weighting of the spectrum plus a second-order weighting of all pairs of spectrum values within a certain frequency range of best frequency. The method allows prediction of rate responses to stimuli with arbitrary wideband spectral shapes, thus providing a direct test of the degree of linearity of spectral processing Auditory-nerve fibers are shown to rely mainly on linear weighting of the stimulus spectrum; however, significant second-order terms are present and are important in predicting responses to random-spectrum shape stimuli, although not for predicting responses to noise filtered with cat head-related transfer functions. The second-order terms weight the products of levels at identical frequencies positively and the products of different frequencies negatively. As such, they model both curvature in the rate versus level function and suppressive interactions between different frequency components. The first- and second-order characterizations derived in this method provide a measure of higher-order nonlinearities in neurons, albeit without providing information about temporal characteristics.