ABSTRACT
Recently, the study of flexible (elastically bendable and plastically bendable) organic single crystals has become a hot research field in crystal engineering. In general, crystal elasticity and plasticity are incompatible with each other. Different from the applications of fluorescent crystals, the applications of room-temperature phosphorescence (RTP) materials generally ignore the crystallographic nature of large single crystals. Herein, we creatively combine elasticity and plasticity based on one RTP crystal 4,4'-dibromobenzil DBBZL. The in-depth study of the irreversible transformation between elastic bending and plastic bending provided important insights into the mechanism of both elastically bendable crystals and plastically bendable crystals in crystal engineering. The DBBZL crystal exhibits elastic bending (reversible) under external stress, whereas it shows plastic bending (irreversible) after excessive bending. Notably, the first phosphorescent optical waveguides of large single RTP crystals are realized not only in straight state, but also in elastic bent state and plastic bent state.
ABSTRACT
BACKGROUND: The Office of Naval Research (ONR) organized a STEM Challenge initiative to explore how intelligent tutoring systems (ITSs) can be developed in a reasonable amount of time to help students learn STEM topics. This competitive initiative sponsored four teams that separately developed systems that covered topics in mathematics, electronics, and dynamical systems. After the teams shared their progress at the conclusion of an 18-month period, the ONR decided to fund a joint applied project in the Navy that integrated those systems on the subject matter of electronic circuits. The University of Memphis took the lead in integrating these systems in an intelligent tutoring system called ElectronixTutor. This article describes the architecture of ElectronixTutor, the learning resources that feed into it, and the empirical findings that support the effectiveness of its constituent ITS learning resources. RESULTS: A fully integrated ElectronixTutor was developed that included several intelligent learning resources (AutoTutor, Dragoon, LearnForm, ASSISTments, BEETLE-II) as well as texts and videos. The architecture includes a student model that has (a) a common set of knowledge components on electronic circuits to which individual learning resources contribute and (b) a record of student performance on the knowledge components as well as a set of cognitive and non-cognitive attributes. There is a recommender system that uses the student model to guide the student on a small set of sensible next steps in their training. The individual components of ElectronixTutor have shown learning gains in previous decades of research. CONCLUSIONS: The ElectronixTutor system successfully combines multiple empirically based components into one system to teach a STEM topic (electronics) to students. A prototype of this intelligent tutoring system has been developed and is currently being tested. ElectronixTutor is unique in its assembling a group of well-tested intelligent tutoring systems into a single integrated learning environment.