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Assessment instruments composed of two-tier multiple choice (TTMC) items are widely used in science education as an effective method to evaluate students' sophisticated understanding. In practice, however, there are often concerns regarding the common scoring methods of TTMC items, which include pair scoring and individual scoring schemes. The pair-scoring method is effective in suppressing "false positives" at the cost of missing possible middle states of progression of student understanding. On the other hand, the individual scoring method captures an undistinguished middle level but is prone to rewarding guessing, which leads to "false positives". In addition, this middle level does not discriminate the progression between knowing the result and explaining the reason, which limits the capacity of drawing meaningful implications from the assessment outcomes. To address the concerns with the current scoring methods, it is valuable to explore new scoring method(s) that can fully utilize the information measured with TTMC items. In this study, a number of scoring models are studied using Rasch analysis on data of a popular TTMC test, the Lawson classroom test of scientific reasoning (LCTSR), collected from four considerably different populations. The results show that the model fit quality of the scoring methods varies with student population and item design. In general, there is no one-fits-all solution; however, given the new information obtained in this study, a three-step process is suggested that can guide the development of new mixed scoring models tailored for a particular population and or test. The evaluation results show that the mixed models produce the most reliable model fitting and better than average goodness of fit. Furthermore, the results in this study also confirm previous studies, which suggest that it is harder to come up with a correct explanation than to just know the answer.

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The Fe-doped TiO2nanocomposites synthesized by a deposition-precipitation method were characterized by X-ray diffraction (XRD), transmission electron microscope (TEM), X-ray photoelectron spectroscopy (XPS), and UV-vis adsorption spectra and then were taken as a new “photosensitizer” for photodynamic therapy (PDT). The photocatalytic inactivation of Fe-doped TiO2on Leukemic HL60 cells was investigated using PDT reaction chamber based on LED light source, and the viability of HL60 cells was examined by Cell Counting Kit-8 (CCK-8) assay. The experimental results showed that the growth of leukemic HL60 cells was significantly inhibited by adding TiO2nanoparticles, and the inactivation efficiency could be effectively enhanced by the surface modification of TiO2nanoparticles with Fe doping. Furthermore, the optimized conditions were achieved at 5 wt% Fe/TiO2at a final concentration of 200 μg/mL, in which up to 82.5% PDT efficiency for the HL60 cells can be obtained under the irradiation of 403 nm light (the power density is 5 mW/cm2) within 60 minutes.

Standardized concept inventories (CIs) have been widely used in science, technology, engineering, and mathematics education for assessment of student learning. In practice, there have been concerns regarding the length of the test and possible test-retest memory effect. To address these issues, a recent study developed a method to split a CI into two equivalent short CIs, which have been shown to provide equivalent mean score measures. However, the previous approach does not fully examine common requirements of test equating. This study extends the existing method with test equating analysis to form a revised algorithm for developing and validating equivalent short CIs. The method is applied to split the Conceptual Survey of Electricity and Magnetism (CSEM) into two half-length CSEMs (HCSEMs). Through a series of test-equating and validation analysis, the HCSEMs are confirmed to measure the same content clusters and the same construct of students' understanding as that of the original CSEM at a similar level of reliability regarding their question design features. Furthermore, a best performing equating function to convert scores among the two HCSEMs and the CSEM is identified through comparisons of four commonly used equating functions. The conversions are further validated using the existing data sets as well as a data set collected from an empirical study using randomized testing. The results confirm that the three CIs can provide equivalent measures in different subpopulations. Overall, the results from this study have shown that the revised algorithm can provide a more complete framework in developing and validating equivalent short CIs. In addition, this method can also be applied to develop and validate parallel CIs in general.