Conditions for the Effectiveness of Multiple Visual Representations in Enhancing STEM Learning

Universal pictures: A lithophane codex helps teenagers with blindness visualize nanoscopic systems

People with blindness have limited access to the high-resolution graphical data and imagery of science. Here, a lithophane codex is reported. Its pages display tactile and optical readouts for universal visualization of data by persons with or without eyesight. Prototype codices illustrated microscopy of butterfly chitin-from N-acetylglucosamine monomer to fibril, scale, and whole insect-and were given to high schoolers from the Texas School for the Blind and Visually Impaired. Lithophane graphics of Fischer-Spier esterification reactions and electron micrographs of biological cells were also 3D-printed, along with x-ray structures of proteins (as millimeter-scale 3D models). Students with blindness could visualize (describe, recall, distinguish) these systems-for the first time-at the same resolution as sighted peers (average accuracy = 88%). Tactile visualization occurred alongside laboratory training, synthesis, and mentoring by chemists with blindness, resulting in increased student interest and sense of belonging in science.

Understanding Polymer Electrodeposition and Conducting Polymer Modified Electrodes Using Electrochemistry, Spectroscopy, and Scanning Probe Microscopy

Conducting polymers are critically important materials in organic electronic platforms relevant to sustainability (organic photovoltaics and organic light-emitting diodes) and wearable electronics (organic electrochemical transistors). However, most chemistry students do not receive formal training in the fundamental properties and extensive characterization of these fascinating materials. Described here are four scaffolded learning modules adapted from the primary literature and designed to build the fundamental understanding and practical skills necessary for productive contribution to emerging research in the field of conducting polymers and conducting polymer modified electrodes (CPMEs). These activities were performed by first-year chemistry graduate students and have been used in the lab to orient and equip new student researchers with the electrochemical, spectroscopic, and spectroelectrochemical skillsets central to working in CPMEs. First year master's students and undergraduate student researchers worked individually to complete data collection, analysis, and interpretation over three 4 h periods with additional time for sample preparation and imaging. Alternatively, one or more of these modules can be adapted and performed by pairs or groups of three over two 4 h lab periods as part of an undergraduate course such as instrumental analysis, polymers, and macromolecules, or as a capstone experience; instructions for these and other modifications are as described herein. If lab equipment and/or available time are limiting factors, sufficient sample data are provided for use as dry laboratories. Through completion of these modules, student researchers learn how to build chemically rational explanations for the electrochemical and spectroscopic signals, to collectively examine data from multiple complementary characterization techniques, and to extract enabling structure-property relationships, all while coming to see themselves as researchers and members of a worldwide scientific community.

The relation of representational competence and conceptual knowledge in female and male undergraduates

Background

Representational competence is commonly considered a prerequisite for the acquisition of conceptual knowledge, yet little exploration has been undertaken into the relation between these two constructs. Using an assessment instrument of representational competence with vector fields that functions without confounding topical context, we examined its relation with N = 515 undergraduates' conceptual knowledge about electromagnetism.

Results

Applying latent variable modeling, we found that students' representational competence and conceptual knowledge are related yet clearly distinguishable constructs (manifest correlation: r = .54; latent correlation: r = .71). The relation was weaker for female than for male students, which could not be explained by measurement differences between the two groups. There were several students with high representational competence and low conceptual knowledge, but only few students with low representational competence and high conceptual knowledge.

Conclusions

These results support the assumption that representational competence is a prerequisite, yet insufficient condition for the acquisition of conceptual knowledge. We provide suggestions for supporting learners in building representational competence, and particularly female learners in utilizing their representational competence to build conceptual knowledge.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40594-023-00435-6.

The impact of multiple representations on students' understanding of vector field concepts: Implementation of simulations and sketching activities into lecture-based recitations in undergraduate physics

Multiple external representations (e.g., diagrams, equations) and their interpretations play a central role in science and science learning as research has shown that they can substantially facilitate the learning and understanding of science concepts. Therefore, multiple and particularly visual representations are a core element of university physics. In electrodynamics, which students encounter already at the beginning of their studies, vector fields are a central representation typically used in two forms: the algebraic representation as a formula and the visual representation depicted by a vector field diagram. While the former is valuable for quantitative calculations, vector field diagrams are beneficial for showing many properties of a field at a glance. However, benefiting from the mutual complementarity of both representations requires representational competencies aiming at referring different representations to each other. Yet, previous study results revealed several student problems particularly regarding the conceptual understanding of vector calculus concepts. Against this background, we have developed research-based, multi-representational learning tasks that focus on the visual interpretation of vector field diagrams aiming at enhancing a broad, mathematical as well as conceptual, understanding of vector calculus concepts. Following current trends in education research and considering cognitive psychology, the tasks incorporate sketching activities and interactive (computer-based) simulations to enhance multi-representational learning. In this article, we assess the impact of the learning tasks in a field study by implementing them into lecture-based recitations in a first-year electrodynamics course at the University of Göttingen. For this, a within- and between-subjects design is used comparing a multi-representational intervention group and a control group working on traditional calculation-based tasks. To analyze the impact of multiple representations, students' performance in a vector calculus test as well as their perceived cognitive load during task processing is compared between the groups. Moreover, analyses offer guidance for further design of multi-representational learning tasks in field-related physics topics.

The Complexity of Reasoning about and with Chemical Representations

External visual representations of chemical entities and processes (chemical representations) play a critical role in chemical thinking and practice. They support reasoning by serving as bridges between the macroscopic world and the chemical models that help us make sense of the properties and behaviors of substances in our surroundings. Consequently, many chemistry education research studies have been carried out to explore and foster students' representational competency in our discipline. Nevertheless, in this Perspective I argue that investigations in this area would benefit from a more in-depth analysis of how the distinctive characteristics of chemical representations affect student reasoning. I identify four dimensions of variation in these representations (iconicity, quantitativeness, granularity, dimensionality) that affect students' ability to interpret, connect, generate, and use chemical representations. I discuss how these features influence the unpacking or packing of information during different types of tasks, affecting sense-making and perceptual competency. Implications for chemistry education research and practice are considered.

A Radial Basis Function Neural Network Approach to Predict Preschool Teachers' Technology Acceptance Behavior

With the continual development of artificial intelligence and smart computing in recent years, quantitative approaches have become increasingly popular as an efficient modeling tool as they do not necessitate complicated mathematical models. Many nations have taken steps, such as transitioning to online schooling, to decrease the harm caused by coronaviruses. Inspired by the demand for technology in early education, the present research uses a radial basis function (RBF) neural network (NN) modeling technique to predict preschool instructors' technology usage in classes based on recognized determinant characteristics of technology acceptance. In this regard, this study utilized the RBFNN approach to predict preschool teachers' technology acceptance behavior, based on the theory of planned behavior, which states that behavioral achievement, in our case the actual technology use in class, depends on motivation, intention and ability, and behavioral control. Thus, this research design is based on an adapted version of the technology acceptance model (TAM) with eight dimensions: D1. Perceived usefulness, D2. Perceived ease of use, D3. Perceived enjoyment, D4. Intention to use, D5. Actual use, D6. Compatibility, D7. Attitude, and D8. Self-efficacy. According to the TAM, actual usage is significantly predicted by the other seven dimensions used in this research. Instead of using the classical multiple linear regression statistical processing of data, we opted for a NN based on the RBF approach to predict the actual usage behavior. This study included 182 preschool teachers who were randomly chosen from a project-based national preschool teacher training program and who responded to our online questionnaire. After designing the RBF function with the actual usage as an output variable and the other seven dimensions as input variables, in the model summary, we obtained in the training sample a sum of squares error of 37.5 and a percent of incorrect predictions of 43.3%. In the testing sample, we obtained a sum of squares error of 14.88 and a percent of incorrect predictions of 37%. Thus, we can conclude that 63% of the classified data are correctly assigned to the models' dependent variable, i.e., actual technology use, which is a significant rate of correct predictions in the testing sample. This high significant percentage of correct classification represents an important result, mainly because this is the first study to apply RBFNN's prediction on psychological data, opening up a new interdisciplinary field of research.

Examining Virtual Manipulatives for Teaching Computations With Fractions to Children With Mathematics Difficulty

As digital technology use increases in K-12 education, greater numbers of strategies become available to support students in mathematics. One technology that provides students diverse representations of mathematical concepts is virtual manipulatives. Although instruction featuring representations with physical manipulatives possesses a large body of research, the virtual form lacks comparable study, particularly with young children experiencing mathematics difficulty or identified with a mathematics learning disability. These students often demonstrate challenges learning integral skills such as fractions that subsequently affect their academic success in future years. This study examined the use of virtual manipulatives paired with explicit instruction and a system of least prompts for teaching computations with fractions to three elementary students with mathematics difficulty. A functional relation was found using a single-subject multiple probe design between the treatment condition and students' accuracy performance solving problems. These results and their implications for the field at-large are discussed.

Detailed bugs or bugging details? The influence of perceptual richness across elementary school years

Visualizations are commonly used in educational materials; however, not all visualizations are equally effective at promoting learning. Prior research has supported the idea that both perceptually rich and bland visualizations are beneficial for learning and generalization. We investigated whether the perceptual richness of a life cycle diagram influenced children's learning of metamorphosis, a concept that prior work suggests is difficult for people to generalize. Using identical materials, Study 1 (N = 76) examined learning and generalization of metamorphosis in first- and second-grade students, and Study 2 (N = 53) did so in fourth- and fifth-grade students. Bayesian regression analyses revealed that first and second graders learned more from the lesson with the perceptually rich diagram. In addition, fourth and fifth graders generalized more with the bland diagram, but these generalizations tended to be incorrect (i.e., generalizing metamorphosis to animals that do not undergo this type of change). These findings differ from prior research with adults, in which bland diagrams led to more correct generalizations, suggesting that the effect of perceptual richness on learning and generalization might change over development.

Drawingvoice 2.0: classroom joint designing and Facebook interactions to develop reflexivity and awareness

Drawingvoice 2.0 is an instructional method of collaborative pencil and paper drawing to use in the school classroom, followed by Facebook interaction on the drawing produced in class. It is based on a participatory and meta reflective approach, explicitly aimed at deconstructing, negotiating, and reconstructing the meaning that students attribute to themselves regarding their professional expectations and educational pathways. In particular, the collaborative pencil and paper drawing allows for the student's emotional symbolisation processes underlying their educational pathway. Drawingvoice 2.0 induces a multidimensional cognitive and meta-cognitive process further supported by the following interaction on Facebook. Therefore, the World Wide Web is the added resource for sharing and deepening the classmates' discussion. Finally, Drawingvoice 2.0 supported structural group interaction and was an important supportive and instructional method to bring about transformational and developmental training practices. As the main result, in our experience, psychology students increased their reflectivity about their strengths and threats in being psychologists within their cultural contexts and potential positive resources underlying their choice. Drawingvoice 2.0 thus enhanced their self-awareness about the lights and shadows of their training and future professional career.

Einfluss visueller Hilfen und räumlicher Fähigkeiten auf die graphische Interpretation von Vektorfeldern: Eine Eye-Tracking-Untersuchung

Ein solides Verständnis physikalischer Konzepte erfordert den Umgang mit multiplen Repräsentationen wie Formeln und Diagrammen zur Bildung kohärenter mentaler Modelle. Bei komplexen Sachverhalten haben Studierende häufig Schwierigkeiten mit solchen repräsentationalen Verknüpfungen und benötigen deshalb instruktionale Unterstützung. In diesem Beitrag wird der Einfluss von zwei Instruktionen (mit und ohne visuelle Hilfen; VH vs. OH) zur graphischen Interpretation eines Vektorfelddiagramms hinsichtlich Divergenz auf die Leistungsfähigkeit von $$N=141$$ N = 141 Studierenden untersucht. Beim Lesen der Instruktion und der anschließenden Aufgabenbearbeitung wurden die Augenbewegungen mit einem Eye-Tracker aufgenommen. Die Ergebnisse zeigen, dass Studierende in der VH-Gruppe ($$N=64$$ N = 64 ) eine bessere Testleistung erzielten als Studierende der OH-Gruppe ($$N=77$$ N = 77 ). Der Unterschied ist am stärksten ausgeprägt für die Studierendengruppen mit hohen und mittelstarken räumlichen Fähigkeiten, die im Vorfeld der Untersuchung mittels eines standardisierten Raumspannentests ermittelt wurden. Die Eye-Tracking-Analysen zum Lesen der Instruktionen zeigen, dass den Studierenden mit visuellen Hilfen die Selektion, Organisation und Integration lernrelevanter Informationen im Sinne der kognitionspsychologischen Theorie multimedialen Lernens besser gelingen als Studierenden der OH-Gruppe. Die Analyse der Eye-Tracking-Daten beim anschließenden Problemlösen ergibt, dass Studierende mit VH-Instruktion ihre Augen systematischer über die Vektorfelddiagramme bewegen, was eine korrekte Anwendung der vermittelten Strategie indiziert. Neben dem modellprüfenden Charakter und der Bedeutung visueller Hilfen zeigt die Studie das diagnostische Potential von Eye-Tracking bei Aufgaben mit hohen Ansprüchen an die kognitiv-visuellen Fähigkeiten.

Graphic Reading Performance of Students with Visual Impairments and Its Implication for Instruction and Assessment

Introduction:

The ability of students to engage with graphical materials supports learning in science, technology, engineering, arts, and mathematics areas. For students with visual impairments, understanding the factors that contribute to the effective interpretation of graphics can promote meaningful access to the curricula.

Methods:

Forty students with visual impairments completed multiple-choice question tasks for five types of graphics presented in their medium of choice and provided difficulty ratings. The teachers of students with visual impairments rated the students on several factors. Statistical analyses investigated the relationship between performance differences and teacher-rated factors.

Results:

Significant differences in performance between print and tactile graphics users were found for bar graph, map, and total correct responses on all tasks. For some tasks, perceived difficulty by tactile graphic users did not align with actual performance. Teachers’ ratings of students who had Individualized Education Program goals for graphics, independence in using graphics, problem-solving ability, mathematics ability, and frequency of engaging with graphics contributed to significant differences in performance across total correct and most individual graphic results.

Discussion:

Although medium type was a significant contributor across graphic types, some teacher-rated variables appeared to mitigate the importance of medium on student performance. Depending on the graphic type, experience, content knowledge, skills with graphics, and confidence and motivation can all affect student performance when interpreting graphics.

Implications for practitioners:

Teachers should provide students with early and frequent opportunities to engage with graphics and support their problem-solving abilities regarding how to engage with different graphic types to enhance their independent use of graphics.

Examining perceptions, selections, and products in undergraduates' learning from multiple resources

BACKGROUND

When learning about complex topics using the Internet, students commonly encounter a multitude of textual, non-textual (e.g., images and graphs), and multimedia (e.g., videos) resources. Yet students' learning from multiple texts and multiple (non-textual) resources (MT-MR learning) has received insufficient consideration in the literature.

AIMS

We examine the associations among (1) undergraduates' conceptions of reasons for multiple resource access, (2) log-data of resource use when completing a MT-MR task, and (3) writing performance.

SAMPLE

Participants were 72 undergraduate students in the United States.

METHODS

Undergraduates were provided with a library of five texts and one video, with the option of accessing supplemental data (e.g., graphs and maps) in association with each resource. Log-data (e.g., time and supplemental data access) of undergraduates' resource use were collected. Undergraduates were then asked to compose a research report and to describe what they considered the purpose of multiple resource access to be.

RESULTS

Four types of conceptions were identified, reflecting a desire to (1) access a lot of information, (2) understand multiple perspectives, (3) corroborate and evaluate information, and (4) develop a personal understanding of a given topic. Undergraduates who considered corroboration and evaluation to be the purpose of multiple resource access were more likely to access more supplemental data sources and performed better on a multiple resource learning task.

CONCLUSIONS

Undergraduates in our sample held conceptions largely similar to, but in some aspects distinct from, those identified by Barzilai and Zohar (Cognit Instruct, 30, 2012, 39). Conceptions were associated with resource access during task completion and with writing performance.

Interpersonal Meaning: Verbal Text–Image Relations in Multimodal Science Texts for Young Children

Verbal text and images constitute the principal semiotic modes interacting to produce interpersonal meanings in multimodal science texts for young children. These meanings relate to pedagogical perceptions about children’s learning. This study examined verbal text–image relations regarding the interpersonal meaning dimensions of address (the way the reader is addressed), social distance (the kind of the relationship between the reader and represented participants), and involvement (the extent to which the reader is engaged with what is represented) in multimodal text excerpts from science-related books for preschool children. The sample consisted of 300 randomly selected units of analysis. For each unit, the verbal and the visual content was analyzed along each dimension, and the relevant verbal text–image relation was determined. Results indicated that regarding address and involvement, relations of convergence appeared significantly more frequently than relations of complementarity and divergence. Concerning social distance, relations of complementarity and divergence were observed more frequently than relations of convergence. Results are discussed in the context of the Systemic Functional Grammar and the Grammar of Visual Design, in the light of the socio-cognitive perspective on science teaching and learning. Implications for the selection, design, and use of multimodal science texts for young children are also discussed.

Teaching Responsible Data Science: Charting New Pedagogical Territory

Although an increasing number of ethical data science and AI courses is available, with many focusing specifically on technology and computer ethics, pedagogical approaches employed in these courses rely exclusively on texts rather than on algorithmic development or data analysis. In this paper we recount a recent experience in developing and teaching a technical course focused on responsible data science, which tackles the issues of ethics in AI, legal compliance, data quality, algorithmic fairness and diversity, transparency of data and algorithms, privacy, and data protection. Interpretability of machine-assisted decision-making is an important component of responsible data science that gives a good lens through which to see other responsible data science topics, including privacy and fairness. We provide emerging pedagogical best practices for teaching technical data science and AI courses that focus on interpretability, and tie responsible data science to current learning science and learning analytics research. We focus on a novel methodological notion of the object-to-interpret-with, a representation that helps students target metacognition involving interpretation and representation. In the context of interpreting machine learning models, we highlight the suitability of "nutritional labels"-a family of interpretability tools that are gaining popularity in responsible data science research and practice.

Cognitive Load Implications for Augmented Reality Supported Chemistry Learning

This paper presents a study about augmented-reality-based chemistry learning in a university lecture. Organic chemistry is often perceived as particularly difficult by students because spatial information must be processed in order to understand subject specific concepts and key ideas. To understand typical chemistry-related representations in books or literature, sophisticated mental rotation- and other spatial abilities are needed. Providing an augmented reality (AR) based learning support in the learning setting together with text and pictures is consistent with the idea of multiple external representations and the cognitive theory of multimedia learning. Using multiple external representations has proven to be beneficial for learning success, because different types of representations are processed separately in working memory. Nevertheless, the integration of a new learning medium involves the risk to hinder learning, in case of being not suitable for the learning topic or learning purpose. Therefore, this study investigates how the AR-use affects students’ cognitive load during learning in three different topics of organic chemistry. For this purpose also the usability of AR learning support is considered and the possible reduction of the influence of the mental rotation on learning success will be investigated.

Representing Variability: The Case of Life Cycle Diagrams

Two foundational concepts in biology education are 1) offspring are not identical to their parents, and 2) organisms undergo changes throughout their lives. These concepts are included in both international and U.S. curricular standards. Research in psychology has shown that children often have difficulty understanding these concepts, as they are inconsistent with their intuitive theories of the biological world. Additionally, prior research suggests that diagrams are commonly used in instruction and that their features influence student learning. Given this prior work, we explored the characteristics of life cycle diagrams and discuss possible implications for student learning. We examined 75 life cycle diagrams from books, including five biology or general science textbooks and 25 specialized trade books focusing on biology for children. We also examined 633 life cycle diagrams from a publicly available online database of science diagrams. Most diagrams failed to show any within-species variability. Additionally, many diagrams had perceptually rich backgrounds, which prior research suggests might hinder learning. We discuss how the design characteristics of diagrams may reinforce students' intuitive theories of biology, which might make it difficult for students to understand key biological concepts in the future.

Effectiveness of Computer-Generated Virtual Reality (VR) in Learning and Teaching Environments with Spatial Frameworks

In this paper, we highlight the benefits of using computer-generated VR in teaching instructional content that have spatial frameworks such as in science, technology, engineering, and mathematics (STEM) courses. Spatial ability scores were collected from a sample (N = 62) of undergraduate and graduate students. Students were required to complete an instructional tutorial in VR and computer desktop screening on DNA molecules, which included necessary information about DNA and nucleotide molecules. Students also completed a comprehensive test about the spatial structure of DNA and a feedback questionnaire. Results from the questionnaire showed media use and satisfaction to be significantly related. The results also showed a significant interaction between spatial ability levels (low, medium, and high) and media used on students’ spatial understanding of the DNA molecules. It may be concluded that VR visualization had a positive compensating impact on students with low spatial ability.

Cognitive Task Analysis for Implicit Knowledge About Visual Representations With Similarity Learning Methods

Visual representations are prevalent in STEM instruction. To benefit from visuals, students need representational competencies that enable them to see meaningful information. Most research has focused on explicit conceptual representational competencies, but implicit perceptual competencies might also allow students to efficiently see meaningful information in visuals. Most common methods to assess students' representational competencies rely on verbal explanations or assume explicit attention. However, because perceptual competencies are implicit and not necessarily verbally accessible, these methods are ill-equipped to assess them. We address these shortcomings with a method that draws on similarity learning, a machine learning technique that detects visual features that account for participants' responses to triplet comparisons of visuals. In Experiment 1, 614 chemistry students judged the similarity of Lewis structures and in Experiment 2, 489 students judged the similarity of ball-and-stick models. Our results showed that our method can detect visual features that drive students' perception and suggested that students' conceptual knowledge about molecules informed perceptual competencies through top-down processes. Furthermore, Experiment 2 tested whether we can improve the efficiency of the method with active sampling. Results showed that random sampling yielded higher accuracy than active sampling for small sample sizes. Together, the experiments provide the first method to assess students' perceptual competencies implicitly, without requiring verbalization or assuming explicit visual attention. These findings have implications for the design of instructional interventions that help students acquire perceptual representational competencies.

Natural Alternatives to Natural Number: The Case of Ratio

The overwhelming majority of efforts to cultivate early mathematical thinking rely primarily on counting and associated natural number concepts. Unfortunately, natural numbers and discretized thinking do not align well with a large swath of the mathematical concepts we wish for children to learn. This misalignment presents an important impediment to teaching and learning. We suggest that one way to circumvent these pitfalls is to leverage students' non-numerical experiences that can provide intuitive access to foundational mathematical concepts. Specifically, we advocate for explicitly leveraging a) students' perceptually based intuitions about quantity and b) students' reasoning about change and variation, and we address the affordances offered by this approach. We argue that it can support ways of thinking that may at times align better with to-be-learned mathematical ideas, and thus may serve as a productive alternative for particular mathematical concepts when compared to number. We illustrate this argument using the domain of ratio, and we do so from the distinct disciplinary lenses we employ respectively as a cognitive psychologist and as a mathematics education researcher. Finally, we discuss the potential for productive synthesis given the substantial differences in our preferred methods and general epistemologies.