The use of verbal report (e.g. "think-aloud") techniques in developing a survey instrument can be critical to establishing an instrument's cognitive validity, which helps ensure that participants interpret and respond to survey items in the manner intended by the survey designer(s). The primary advantage of utilizing a verbal cognitive validation protocol is having evidence that survey items are interpreted by participants in the same way the researcher intended before the instrument is administered to a large sample. Think-aloud protocols have been used to accomplish different goals in a variety of fields, including engineering education where thinkalouds are commonly used in problem solving research. While think-alouds have been used by engineering education researchers, the engineering education literature includes few resources for researchers regarding the use of these protocols with respect to large-scale survey development and refinement. In this paper, we present a protocol based on elements of thinkalouds conducted inside and outside the engineering education domain. By presenting results and examples from our own experience suing this protocol, we aim to provide a cognitive validation model which may be useful to engineering education researchers designing their own survey instruments.By following the model outlined in this paper, participants in our study verbalized several issues of concern when interacting with our web-based survey. These issues ranged from minor grammatical errors to serious cognitive mismatches which caused participants to interpret and/or respond to items differently than we intended. Participants were asked for suggestions to correct these issues, and changes were made to the survey based on this feedback. The survey was retested in two additional iterations of think-aloud sessions with new participants to ensure the revisions successfully remedied the issues encountered by previous participants. Finally, the refined survey was pilot tested and subsequently reviewed by an expert in the field before being administered at seven institutions. This paper includes evidence and specific examples of how the cognitive validation model resulted in a refined survey instrument, as well as recommendations for other engineering education researchers wishing to employ similar techniques in designing and validating survey instruments.

is helping develop a new Engineering Leadership Program to enable students to bridge the gap between traditional engineering education and what they will really experience in industry. With a background in both engineering education and design thinking, her research focuses on how Hispanic students develop an identity as an engineer, methods for enhancing student motivation, and methods for involving students in curriculum development and teaching through Peer Designed Instruction.

Organicallycoated inorganic nanoparticles were synthesized to produce photoluminescent nanocomposites based on a polymethyl methacrylate (PMMA) matrix. The nanoparticles comprised organic ligands (acetylsalicylic acid, ASA, and 2-picolinic acid, PA) attached to the lanthanum trifluoride (LaF3) host crystals that were doped with optically active terbium III (Tb3+) and synthesized using solution-based methods. The ligands were employed to functionalize the surface of Tb3+:LaF3nanocrystals to aid in dispersing the nanoparticles. In order to confirm the presence of the constituents within the inorganic-organic system, the nanoparticles were characterized by infrared spectroscopy and energy-dispersive X-ray spectroscopy. Absorption peaks observed from infrared spectroscopy for all the polymer nanocomposites loaded with organic surface treated nanocrystals exhibited peaks that were not present in undoped PMMA but were characteristic of the dopant and the ligand.

Organic ligand surface-treated Tb 3+ :LaF 3 was synthesized in water and methanol for subsequent incorporation into polymethyl methacrylate (PMMA) via solution-precipitation chemistry in order to produce optically active polymer nanocomposites. Nanoparticle agglomerate diameters ranged from 388 ± 188 nm when synthesized in water and 37 ± 2 nm when synthesized in methanol. Suspension stability is paramount for producing optically transparent materials. Methanol nanoparticle synthesized at a pH of 3 exhibited the smallest agglomerate size. Optical spectroscopy, dynamic light scattering, transmission electron microscopy, scanning transmission electron microscopy, and zeta potential analysis were used to characterize the particles synthesized.

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