Can human-machine feedback in a smart learning environment enhance learners' learning performance? A meta-analysis.

Objective: The human-machine feedback in a smart learning environment can influences learners' learning styles, ability enhancement, and affective interactions. However, whether it has stability in improving learning performance and learning processes, the findings of many empirical studies are controversial. This study aimed to analyze the effect of human-machine feedback on learning performance and the potential boundary conditions that produce the effect in a smart learning environment.

Chiral cyclic []spirobifluorenylenes: carbon nanorings consisting of helically arranged quaterphenyl rods illustrating partial units of woven patterns.

Chiral cyclic []spirobifluorenylenes consisting of helically arranged quaterphenyl rods, illustrating partial units of woven patterns, were designed and synthesized as a new family of carbon nanorings. The synthesis was accomplished by the Ni(0)-mediated Yamamoto-coupling of chiral spirobifluorene building blocks. The structures of the cyclic 3-, 4-, and 5-mers were determined by X-ray crystallographic analysis.

A reverberation-ray matrix method for guided wave-based non-destructive evaluation.

The paper presents an application of the reverberation-ray matrix (RRM) method for guided wave-based non-destructive evaluation (NDE). An exact analytical model for elastic wave propagation in multilayered anisotropic composites is developed with the RRM method. Dispersion curves, namely phase and group velocities varying with frequencies, can be calculated based on the analytical model, which are critical to the guided wave-based NDE.