Herein, we report the synthesis and characterization of Ce(III)-doped UiO-66 nanocrystals, revealing their potential to efficiently remove organic dyes such as methylene blue (MB), methyl orange (MO), Congo red (CR), and acid chrome blue K (AC) from aqueous solutions. Specifically, the room-temperature adsorption capacities of Ce(III)-doped UiO-66 equaled 145.3 (MB), 639.6 (MO), and 826.7 (CR) mg g⁻¹, exceeding those reported for pristine UiO-66 by 490, 270, and 70%, respectively. The above behavior was rationalized based on zeta potential and adsorption isotherm investigations, which revealed that Ce(III) doping increases the number of adsorption sites and promotes π–π interactions between the adsorbent and the adsorbate, thus improving the adsorption capacity for cationic and anionic dyes and overriding the effect of electrostatic interactions. The obtained results shed light on the mechanism of organic dye adsorption on metal–organic frameworks, additionally revealing that the synergetic interplay of electrostatic, π–π, and hydrophobic interactions results in the operation of two distinct adsorption regimes depending on adsorbate concentration.

Game-based learning supported by mobile intelligence technology has promoted the renewal of teaching and learning models. Herein, a model of Question-Observation-Doing-Explanation (QODE) based on smart phones was constructed and applied to science learning during school disruption in COVID-19 pandemic. In this study, from the theoretical perspective of cognitive-affective theory of learning with media, Bandura’s motivation theory and community of inquiry model, self-report measure was used to verify the effect of students’ scientific self-efficacy and cognitive anxiety on science engagement. A total of 357 valid questionnaires were used for structural equation model research. The results indicated that two types of scientific self-efficacy, as indicated by scientific learning ability and scientific learning behavior, were negatively associated with cognitive anxiety. In addition, cognitive anxiety was also negatively correlated to four types of science engagement, as indicated by cognitive engagement, emotional engagement, behavioral engagement, and social engagement through smartphone interactions. These findings provide further evidence for game-based learning promoted by smart phones, contributing to a deeper understanding of the associations between scientific self-efficacy, cognitive anxiety, and science engagement. This study points out that the QODE model is suitable for implementing smart mobile devices to students’ science learning.