Published research on pre-college students’ and teachers’ nanoscale science, engineering, and technology learning

4.1 Characterization of articles for review

We found a total of 51 peer-reviewed journal articles on pre-college NSET education. Each member of the author team read each of the 51 articles. From our initial reading and discussion, we developed five categories for coding the central focus/purpose of each article: (1) empirical studies on pre-college student and/or teacher learning and cognition; (2) descriptions of pre-college programs, lessons, and/or activities that include an evaluative assessment of the learning materials/environment; (3) descriptions of pre-college programs, lessons, and/or activities only; (4) research reviews, position papers, and theoretical papers; and (5) other research focus (including assessment instrument development; studies on pre-college teachers’ or students’ perceptions, beliefs, and/or attitudes but not related to a specific program, lesson, or activity). Each of the author team members independently categorized each article and compared results. When one member was in disagreement, we discussed the article and came to a consensus. We found 26 empirical studies on pre-college student and teacher learning; eight descriptions of pre-college programs, lessons and/or activities that include an evaluative assessment of the learning materials/environment; four descriptions of pre-college programs, lessons, and/or activities; five research reviews, position papers, and theoretical papers; and eight other research articles. Figure 1 displays the distribution of articles by focus of article and year published.

Figure 1

Pre-college NSET articles categorized by focus and year published.

4.2 Data analysis

We characterized each of the 26 articles that reported an empirical study of pre-college student and/or teacher learning and cognition according to the following components: study participants in terms of grade level, NSET content focus, research questions, pedagogical approach of intervention (when applicable), learning measures/data, and findings. We also were interested in the nature of the content learned, specifically whether the content involved conceptual understanding (definition) or was simply an assessment of factual knowledge and included this characterization within the narrative of the findings. We then synthesized findings across articles according to NSET content, organizing the findings using the Big Ideas of Nanoscale Science and Engineering [11] as an organizational framework (henceforth, “big ideas”).

5.1 Learning research on size and scale

The big idea that has received the greatest attention in NSET learning-related research is size and scale. Fifteen out of the 26 articles we reviewed examined size and scale, either as the main focus of the study or as one of several big ideas. Stevens et al. [11] refer to the construct of size as “the extent or bulk amount of something” (p. 5). Scale refers to the characterization of broad ranges of size into identifiable “worlds” (e.g., cosmic, micro, and nano), by unit of measurement, tools, or landmark objects [13]. Learning research in size and scale has particularly focused on individuals’ different conceptualizations and how those conceptualizations vary with age, grade level, everyday experience, culture, and expertise in STEM disciplines.

5.2 Learning research on concepts related to size-dependent properties

A fundamental principle related to nanoscale materials, and perhaps the most defining of all nanoscale-related phenomena, is that there are thresholds of size across which properties of a material are often governed by size. Four of the studies in this review examined students’ and/or teachers’ conceptions of size-dependent properties. The most common theme among studies that focused on or included size-dependent properties is the surface area and volume (SA/V) relationship. While nanoscale phenomena relating to surface area and volume relationships can best be understood in terms of the atomic and molecular composition of matter, forces, and thermal energy, we found that treatment of these concepts was generally underutilized in learning. The following studies, however, illuminate the fact that understanding factors related to size-dependent properties poses challenges to both learning and teaching, requiring individuals to push the limits of their abilities to visualize and manipulate objects in multiple dimensions.

A testament to the difficulty in understanding the significance of how and why size can affect nanoscale materials, Bryan et al. [27] analyzed secondary teachers’ understanding of size-dependent properties in a year-long nanoscience professional development program. Teachers completed multiple laboratory activities and investigations of size-dependent properties, among them the synthesis and manipulation of a ferrofluid, the fabrication of a gold particle biosensor, and the synthesis and characterization of quantum dots. While researchers anticipated that following instruction, teachers’ explanations of size-dependent phenomena would be supported with rationale based on forces, aspect ratios, atomic structure, and thermal energy, fewer than 20% included this level of sophistication. While many of the teachers cited examples of nanoscale properties that differ as a function of size, they were less likely to explain the underlying concepts how and why these differences occur.

5.3 Learning research on the nature of matter

Understandings associated with the nature of matter can be described as core and precursor concepts for NSET education. Although research related to pre-college students’ conceptions regarding the nature of matter is extensive in science education, until recently, very few studies have situated the study of nature of matter in an NSET context. This contextualization is relevant because at the nanoscale, matter exhibits novel and unexpected properties, and resulting behaviors and interactions may be counterintuitive for a novice learner. In this review, we found two articles that directly addressed students’ learning about states of matter in an NSET-related context.

In a study that examined learning within a middle school microscopy camp, Penn, Flynn, and Johnson assessed the students’ macroscopic, microscopic, and symbolic conceptions of particles [30]. On the pretest, researchers identified three types of representations: acceptable representations of clear atomic structures where atoms had consistent sizes and shapes (n=0), unacceptable representations with no evidence of atomic structure (n=9), and unclear representations where the drawings included some indication of atomic structure but depicted that atoms lacked consistent size and shapes (n=1). On the posttest, researchers identified shifts in the same three types of representations: acceptable representations of clear atomic structures where atoms had consistent sizes and shapes (n=8), unacceptable representations with no evidence of atomic structure (n=1), and unclear representations where the drawings included some indication of atomic structure but depicted atoms lacked consistent size and shapes (n=1). These results suggest that students were able to develop an improved understanding of the idea that the size of an object’s atoms is independent of the size of the object [30].

In a study by Stevens et al. [31], the researchers identified core concepts associated with models of the structure, behavior, and properties of matter through a hypothetical learning progression. Drawing on the work of Duschl, Schweingruber, and Shouse in Taking Science to School[32], they defined learning progressions as describing how learners may potentially construct a more sophisticated understanding of a concept over time. This might be of a sequential nature, where the progression elaborates how the understanding of one concept supports and forms the foundation for the learning of another. Alternatively, the learning progression may describe how the learner constructs a more complex model, where the knowledge of a concept becomes more sophisticated, incorporating broader ideas and connections to related topics [31]. Learning progressions qualitatively differentiate among levels of understanding, articulating the knowledge needed by students prior to developing a sophisticated understanding (herein called lower anchor) as well as expected sophisticated knowledge and ideas (herein called upper anchor). In their study, Stevens et al. defined the lower anchors and upper anchors for the hypothetical learning progression, followed by a delineation of the specific science content between the lower and upper anchors for atomic structure and related electrical forces.

To identify middle school, high school, and undergraduate students’ (n=73) levels of understanding of (a) the structure and properties of matter and the sources of those properties and (b) the atomic model and the forces and interactions occurring between atoms and molecules, the researchers conducted semi-structured interviews. They found that 69 students fit the lower levels of their identified empirical progression for atomic structure including ideas of electron cloud model (n=15), Bohr/solar system model (n=13), protons and neutrons located in the center of the atom and electrons on the outside (n=29), atoms made of protons, neutrons, and electrons (n=35), atoms containing some components (n=50), atom as a sphere (n=63), and do not know (n=10). Three students who did not fit the learning progression were able to describe a solar system model of the atom but could not identify the components of the atoms (i.e., protons and neutrons). Another student described an electron cloud-like model of the atom but could not mention the names of the sub-atomic particles [31].

Regarding ideas associated with electrical forces, 35 students attempted to provide an explanation of why sodium and chlorine interact to form Cl₂ and NaCl and to describe the interactions that happen between atoms in these substances. Stevens et al. [31] identified in their empirical progression understandings such as the type of element that determines the electron configuration (n=8), valence electrons that are involved in interactions (n=18), electrons as the mediating components of interactions (n=26), electrical forces governing such interactions (n=3), an unspecified force governing such interactions (n=5), and do not know (n=40). Students placed at the lower levels of the empirical progression described an unspecified force as causing interactions between atoms, while other students identified electrical forces and attraction and repulsion between particles as the mechanisms responsible for interactions between atoms. Students placed in the most advanced levels of the progression identified the place of the element in the periodic table as related to the inter-atomic interactions. Overall, these findings as related to student learning of the structure and properties of matter suggest that many middle school and high students lack a working understanding of these concepts, limiting their ability to effectively integrate new knowledge structures needed when learning new NSET-related concepts [31].

5.4 Learning research on forces and interactions

Two of the articles we found examined the big idea of forces and interactions. These studies focused on the forces most influential in determining the behavior of substances chemically and physically at the nanoscale – electromagnetic forces. Höst et al. [33] examined the following: (1) students’ pre-intervention conceptions about electric fields and how their conceptions were applied to a molecular context and (2) the influence of interacting with the multisensory visuohaptic model on students’ conceptual understanding of electric fields around molecules. Prior to the learning intervention, the researchers conducted a written pre-assessment in which five upper secondary students described their conceptual understanding of electric fields and their application to molecular contexts by means of a written assessment. Findings from the pre-assessment indicated that only one student was able to meaningfully associate field lines to the charge distribution in a water molecule. The other four students were able to convey scientifically accurate understandings of an electric field but failed to apply this concept to a molecular context. Similarly, one student failed to identify that electric fields are associated with nonpolar molecules as well as polar molecules [33].

Ideas associated with electric fields around molecules were taught using a multisensory visuohaptic virtual environment where a molecule is visually rendered along with a semitransparent visual rendering of the van der Waals surface of the molecule. While students interacted with the visuohaptic model, researchers performed a think-aloud exercise and collected user analytics of students’ interaction with the model. In their analysis, researchers found that tactile interaction with the model may result in the integration of the field knowledge with molecular charge distribution that allowed learners to merge physical and chemical concepts that are usually taught separately [33].

In a study by Sockman et al. [34], educational experiences related to static forces in nature were contextualized in the mechanisms associated with the ability of a gecko to adhere to surfaces despite the effect of gravity. In this context, the associated main learning objective was for students to identify what are the factors that affect the strength of the contact forces between interacting surfaces. The researchers developed a lesson called NanoLeap where students had to make observations and interpretations of how the gecko’s foot interacts with surfaces and the factors that affect the strength of the contact forces between interacting surfaces. The effectiveness of the NanoLeap unit in helping students identify factors that affect the strength of the contact forces between interacting surfaces was evaluated by means of an essay assessment prompting students (n=100) to demonstrate their understanding about the underlying phenomena of gecko adhesion. Four themes were identified related to language patterns students used in response to the four prompts described above. Sockman et al. [34] concluded that the greatest common understandings among students were the surface-to-surface interactions between the gecko’s setae and spatula. The greatest misunderstandings were related to knowledge of electrical forces and their role in gecko adhesion.

5.5 Learning research on self-assembly

The big idea of self-assembly has been described as a complicated array of phenomena (i.e., entropy, enthalpy, random molecular motion, and intermolecular attractions) working together under specific conditions in which materials spontaneously assemble into organized structures [11, 35]. Self-assembly is an important idea for pre-college NSET education because it is not only a process used to advance the progress of nanotechnology but also one through which natural structures on every scale are built [11].

One study in this review focused on the learning of self-assembly [35]. In this study, concepts about self-assembly were taught following two approaches: a hands-on laboratory experiment and the use of computer simulations. The hands-on laboratory experiment consisted of foam pieces (squared and circular) with magnets attached to them, floating in water. Foam pieces behave in a manner similar to electron clouds of adjacent atoms. Students were engaged in a process of experimentation where they hypothesized the forces that drive self-assembly. A second teaching method was the use of a computer simulation that represents the forces that are acting upon the atoms in examples such as insulin dimmers, fibroin fibers, microtubule rings, and formation of a monolayer [35].

A total of 120 high school students were exposed to the hands-on laboratory experiment (HOLab) described above, and half of them were also exposed to the computer simulation (CSim) as part of homework assignment. By means of an open-ended question that asked students to explain why small objects can spontaneously self-assemble into orderly structures whereas big objects could not self-assemble normally, the researcher identified five categories of explanations: repelling and polarity, charge and electronegativity, attraction and stickiness, intramolecular attraction, and responses that did not identify any factors other than size. The findings suggested that the HOLab reinforced the concepts of repulsion, having most of the students choosing responses as related to repelling, polarity, charge, and electronegativity as explanations, whereas the CSim advanced this concept to include intermolecular attractions having most of the students choosing responses as related to stickiness, attraction, and intermolecular attraction [35].

5.6 Learning research on tools and instrumentation

A big idea of tools and instrumentation at the nanoscale includes the idea that the tools used to visualize and manipulate matter at this scale (e.g., scanning probe microscope and atomic force microscope) are different from those used at other more familiar scales [11]. Thus, an important learning objective for pre-college NSET education is to identify and describe different types of microscopes and their limitations, as well as describe how the atomic force microscope (AFM) works [36]. In this review, we found four studies that focused primarily on pre-college learning of tools and instrumentation.

Learning gains associated with concepts and practices of tools and instrumentation have been measured using a variety of instruments and with two different populations (teachers and middle school and high school learners). Blonder [37] analyzed teacher knowledge about their appropriate use of vocabulary and depth of understanding of how the AFM works. She compared the performance of two groups of seven teachers each; one group had previous knowledge of NSET, and the other group members were NSET novice learners. Blonder found that teachers from both groups demonstrated significant increase in content knowledge, demonstrating richer vocabulary use as related to AFM after instruction. They also learned new and fundamental concepts regarding the AFM.

Jones et al. [36] analyzed 50 high school students’ knowledge about the functioning of an AFM and the limitations of atomic force microscopy. They used constructed response questions that asked students to describe the nanoManipulator and AFM and to identify and describe different types of microscopes and students’ newspaper reports. Before instruction, about 70% of the students were only able to name the light microscope, and another 20% were able to name the electron microscope. After instruction, 25% of students named the light microscope, 50% of students named the AFM, and 21% of students named the electron microscope. In addition, students’ reports also included knowledge of how the AFM operates, the impact of the tip size on the images it produces, and the potential to use it to ask new scientific questions. Finally, about 25% the students described how the different-size tips alter the image of the sample visualized.

Harmer and Columba-Piervallo [38] engaged more than 100 sixth graders in a problem-based inquiry learning experience in which online materials, readings, and class sessions, along with remote access to a scanning electron microscope, were provided. Using the remote microscope, students analyzed samples and contributed with micrographs to a research database. By means of a pretest and posttest assessment, researchers identified significant differences in responses to questions associated with the uses and functionality of the scanning electron microscope. Specifically, students were able to identify that electrons help create images in the electron microscope and that an energy dispersive spectrometer was the tool in the scanning electron microscope that could identify elements in a sample.

Similarly, Ristvey and Pacheco [39] provided 21 high school teachers with hands-on experiences with a mobile AFM and a scanning tunneling microscope to image a microchip, Staphylococcus aureus, a polymer thin film, carbon atoms on the surface of a sample of highly ordered pyrolytic graphite, and a skin cross section. From the pretest to posttest assessments, teachers demonstrated learning gains on the big idea of tools and instrumentation (mean average score improved from 61% to 68%). Specifically, teachers learned the following: (1) the scanner moves the sample or the sensor to probe the sample surface; (2) the sensor detects the cantilever deflection, (3) the feedback system regulates the force interaction; and (4) the controller electronics records movements, controls the feedback loop, and sends the measured data to the computer.

5.7 Learning research across multiple big ideas

In addition to studies that focus on students’ and teachers’ conceptions within a single big idea, a few studies have examined teacher’s content knowledge across a spectrum of NSET topics. For example, Kumar [40] conducted a study of NSET “general knowledge” (p. 20) of 109 prospective elementary and middle school science teachers who were enrolled in an undergraduate science teacher preparation course. Using the 10-item, multiple-choice “Nano Quiz” from the National Institute of Standards and Technology, he found that the prospective teachers, scoring an average of 6.13 out of 10 (SD=1.34), lacked an understanding of the physical scale of NSET and of the etymology of the term “nano”. However, as the author himself stated in his discussion, the finding must be interpreted with caution. In particular, the Nano Quiz is not an assessment of conceptual knowledge but rather simple definitions and discreet facts (e.g., “What is a qubit?”, “What is a Bose-Einstein condensate?”). Nonetheless, the findings highlight the necessity for prospective science teachers to develop an understanding of some general NSET concepts, particularly regarding the physical scale of nanoscience and nanotechnology, if they are to effectively design and implement NSET instruction at the pre-college level.

In the context of a sustained-contact NSET professional development program, Bryan et al. [27] examined teachers’ learning of NSET concepts as well as the durability of their learning across the following topics: (a) defining and describing the nanoscale (material properties and behavior); (b) size and relative scale; (c) tools of the nanoscale (scanning probe microscopy); (d) size-dependent properties (optical and magnetic); (e) structure and design of materials (allotropes, fullerenes, and self-assembly); and (f) models and modeling. Twenty-four teachers participated in a yearlong sustained contact professional development program that included an intensive 2-week (80+ h) institute. Participants completed a 24-item pre-test, post-test, and delayed posttest that consisted of free response, matching, fill-in, and multiple choice questions, as well as questions asking for the construction of diagrams, graphs, or models, with supporting arguments of evidence or rationale. Participants showed significant gains from pretest to post- test, as well as between posttest and delayed test (delayed test administered 8 months after posttest). In addition, based on lesson plans that teachers submitted, the lesson topics taught were matched with the test items that were most likely to be covered in those lessons. Participants’ performance did not differ significantly on the delayed test between taught vs. non-taught items. Furthermore, performance on those same taught vs. non-taught items on the pretest versus the posttest also showed no significant differences. In other words, the teachers did not show a systematic bias toward teaching topics they found either particularly easy or particularly difficult during the workshop.

Studies that provide an overview of teacher knowledge or studies that describe how teachers integrate related NSET topics and ideas are relevant since most of the research conducted so far explores big ideas separately. This study highlights the need to examine and measure teachers’ knowledge as they learn about NSET, particularly as the number of NSET professional development programs, workshops, and activities increases.

5.8 Learning research on teachers’ pedagogical content knowledge

The learning studies reviewed to this point have been organized according the big ideas of NSET and have summarized both pre-college students’ and teachers’ learning of NSET content. However, in the realm of teacher learning, there is an additional dimension of knowledge that is integrally related to teachers’ development of knowledge for teaching NSET in pre-college classrooms: pedagogical content knowledge (PCK) – that is, knowledge about learners, curriculum, instructional strategies, and assessment to transform content knowledge into effective teaching [41].

Teachers undeniably play a pivotal role in the integration of contemporary, cutting-edge science in the pre-college classroom. It is an intuitive notion that teachers must have a strong, flexible, and coherent understanding of command of NSET subject matter if they are to be able to facilitate students’ learning of NSET concepts. Several studies reviewed in the previous sections of this article have addressed a critical aspect of teachers’ NSET learning – NSET content learning (i.e., size and scale [14, 19]; logical thinking and visual-spatial skills related to surface area to volume relationships [29]; tools and instrumentation [37, 39]). Yet, content knowledge alone is not sufficient for effective teaching. In fact, decades of research have shown that a significant component of teacher learning must include the expansion and elaboration of PCK [41]. Therefore, an aspect of NSET learning research that should not be overlooked is teacher learning, specifically the development of PCK for teaching NSET concepts in pre-college classrooms. In this section, we review a handful of studies that examine aspects of teachers’ PCK.

A crucial part of teachers’ PCK for teaching NSET concepts relates to knowledge of models and modeling (e.g., drawings, analogies, computer simulations, and 3-D models). Building, revising, and manipulating models are an inherent component of science and engineering practices. At the pre-college level, teachers should understand that models are particularly critical to the advancement of NSET in that they allow students to visualize structures, construct hypotheses, explain phenomena, and articulate and communicate ideas about concepts at a scale that is otherwise unreachable. In pre-college NSET education, models also serve as a pedagogical tool for teachers. For NSET education, teachers must learn to use models to not only represent and organize salient features of the content to be learned but also provide a means for students to investigate NSET phenomena in the process of learning target concepts.

Daly and Bryan [42] examined 18 secondary science teachers’ reported practices of model use in NSET education after the teachers had participated in a sustained-contact professional development program offered by the NCLT. From an analysis of implemented lesson plans, responses to a written survey on model use, and post-lesson implementation reflective writings, they found that teachers reported four different uses of models for NSET instruction: (1) tool for visualization, (2) product of a student’s design, (3) representation for student critique, and (4) means for investigation. The most common use of models was for visualization – that is, for students to see, watch, and/or touch a model. When teachers used models as tools for visualization, they described teaching strategies that were predominantly teacher-centered and transmission-focused. On the other hand, teachers who employed models for design, critique, and investigation described strategies in which students used models to synthesize, evaluate, and convey their own ideas through the act of designing a representation of their understanding of NSET phenomena [42].

In a case study of two secondary science teachers’ PCK development, Wischow et al. [43] examined how the teachers’ PCK both influenced and was influenced by their integration of NSET content into their science curriculum. Prior to implementation of NSET lessons in their science classroom, both teachers took part in a yearlong professional development program developed and implemented by the NCLT. Data included two semi-structured interviews per participant, videotaped classroom observations and field notes, teachers’ written lesson plans, and teachers’ reflective narratives. The suite of data sources was designed to capture a holistic picture of the teachers’ PCK and construct a “PCK map” to articulate the relationship between teaching orientations, knowledge of science curricula, knowledge of students’ understandings of nanoscale phenomena, knowledge of instructional strategies, and knowledge of assessment for each teacher. Analysis showed that teaching NSET provided a context in which the teachers made shifts in their science teaching orientations. In both case studies, teachers displayed elements of didactic/content mastery and discovery teaching orientations. Both teachers also strengthened their overall domain-specific content knowledge and connections between areas of their content domain by implementing novel content in their classrooms. However, PCK maps illuminated that assessment was one of the PCK knowledge bases that played little to no role in how teachers developed their NSET lessons [43].