Awareness and Empowerment: Teaching with Metacognition to Enhance Learning in Higher Education

A simple definition of metacognition is thinking about thinking. The following proposal describes a recent study about how professors view teaching and learning their subject. The research questions are: Do professors’ gender, years of experience, and the level at which they teach (graduate vs. undergraduate) affect the way they think about learning and the teaching strategies they implement? How does teacher training affect how professors perceive learning and the teaching strategies that they implement? Is there any correlation between professors’ perception of learning vs. teaching strategies they use? A questionnaire that collects professors’ responses to learning and teaching strategies was distributed in five colleges in Pennsylvania. The results of the study indicates that there are some differences in the frequencies that professors use some of the teaching strategies and how they perceive the importance of some learning elements. For example more direct instruction and memorization were ranked as important by professors who teach undergraduate vs graduate and by professors who has not been through any teaching preparation programs, while higher rank for evaluating thinking process and students engagement were reported by professors who went through teacher preparation program. In short, Professors’ characteristics such as being in teacher training, level in which the professors teach (graduate and undergraduate) and other variables correlated with the way professors ranked the various items and thus the way they perceive learning. As teachers, we always seek both to enhance the learning process of our students and our teaching strategies to support the learning process. Thus such studies are needed not just to explore strategies, but also to help us reflect on what we do as professors to help our students learn better. Audience of this poster will be able to complete the survey and reflect on their teaching strategies and how they view learning. If metacognition, as research indicates, enhances learning, then it is important for professors from various backgrounds and subject matters to be aware of and to learn how to teach metacognitively. I am hoping that the study outcomes will stimulate professors to reflect on their teaching strategies, perception of how their studens learn and how this affects their work. The study was sponsored by a grant from Foundation through SEPCHE

The sanctified lie : form and content in the art of Oscar Wilde

This study seeks to show that in the work of Oscar Wilde, form and content, though manifestly separate, are latently connected. In Wilde's aesthetics, form and content are more than mere critical generalities---they are also metaphors for, respectively, art and nature, order and chaos, two conflicting but interdependent principles. Form in Wilde's work is a metaphor for the artist's defense against the largeness and ambiguity of nature and life. Therefore, to create, Wilde needs to insist on form over content, art over nature. Form in Wilde's work manifests itself in a deliberately artificial style, a style revealed by, for example, epigrammatic dialogue and posing of characters. However, because of this emphasis on form, nature and life will make an uncanny figurative return in Wilde's fiction, a return symbolized, for instance, by emotional ambivalence, intellectual ambiguity, and even acts of murder. In Wilde, form and content are interdependent because the content is latent in the principle of form, which stands for the human struggle against the perceived disorder of nature and life, a struggle which nevertheless is revelatory of that same chaos

How the Interaction between Cognition, Behaviors & Emotions Affects Learning Preference of Adults in Higher Education

The following research studies the relationship between cognition, behaviors and emotions as adults in higher education learn new material. It asks about students’ preference in designing and planning classroom activities with various cognitive complexities to enhance learning. The data was collected from graduate students registered in educational research course. Research usually raises some anxiety since for most education students the topic is out of comfort zone. The various cognitive levels of complexity bring up feelings and behaviors that are best dealt with by engaging students as partners in the learning process through support from peers (scaffolding) and the creation of a safe environment. This is an interactive presentation that engages participants in various activities. Feedback from the audience will be appreciated and will contribute to the continuation and development of our study. Participants in this session will leave with some tools to implement in their classrooms

Multiple forms of carboxylesterases in the green bean (Phaseolus vulgaris L.) and pea (Pisum sativum L.)

Esterase activity of an aqueous extract of the green bean was separated into fourteen bands, while aqueous extracted pea esterases revealed seven bands, by polyacrylamide-gel electrophoresis. The fourteen bands of bean esterase activity formed three groups; slow, intermediate and fast moving. α-Naphthyl acetate, propionate, and n-butyrate and AS naphthol acetate were hydrolyzed at various rates by the bean and pea esterases. No hydrolysis of β-naphthyl laurate was observed, indicating the absence of a lipase in the aqueous extracts of these vegetables. Since all the esterase bands active toward α-naphthyl acetate were inhibited by organophosphorus compounds (diisopropylphosphorofluoridate, diethyl p-nitrophenyl thiophosphate and diethyl p-nitrophenyl phosphate), these esterases were classified as carboxylesterases (carboxylic ester hydrolase, EC 3.1.1.1). To study the carboxylesterases of the green bean in greater detail, a protamine sulfate treated aqueous extract was separated into three fractions (S₁, S₂ and S₃) by chromatography on Sephadex G-100. Subsequent analysis of each fraction by polyacrylamide-gel electrophoresis demonstrated the presence of the slow moving group in fraction S₁, slow and intermediate moving groups in fraction S₂ and the fast moving group in fraction S₃. Hence, these studies suggest that the three groups of esterase activity in beans were dissimilar in molecular size and the relative molecular size was slow > intermediate > fast moving group. Chromatography of fraction S₁ on carboxymethyl (CM) cellulose with sodium chloride linear-gradient elution resulted in three fractions (CM₁, CM₂ and CM₃). Similarly, fraction S₂ yielded three fractions (DE₁, DE₂ and DE₃), while fraction S₃ produced two fractions (DE₄ and DE₅), by chromatography on microgranular diethylaminoethyl (DEAE) cellulose. Polyacrylamide-gel electrophoresis revealed the presence of the first three bands of the slow moving group in CM₁ and only the first two bands in CM₂. DE₁ possessed mainly the first two bands and DE₂ the last two bands of the five bands in the slow moving group. The five bands of the intermediate moving group of esterase activity was found only in fraction DE₃. The first two bands of the four bands of the fast moving group were separated into fraction DE₄, while the last two bands were in DE₅. Nine substrates and various concentrations of three inhibitors were used to characterize some of the fractions obtained from ion-exchange chromatography. Although most of the fractions hydrolyzed the substrates used in this study, each fraction differed to some extent in substrate specificity. Inhibitor studies indicated the presence of a sensitive and a resistant component of esterase activity in each fraction studied. These results suggest that the esterase fractions were composed of two enzymes. To account for the fourteen bands of esterase activity a hypothetical model of polymers consisting of two monomers was proposed. This hypothesized model suggests that the slow moving group contained six pentamers, the intermediate group five tetramers and the fast moving group four trimers. Most characteristics of the carboxylesterases of beans observed in these studies could be explained on the basis of the hypothetical model

High School Teachers’ Perceptions Regarding Inquiry-Based Science Curriculum in the United States, Georgia, and Israel

This study explores high school science teachers’ perceptions and current practices of inquiry-based science curriculum and the challenges facing teachers in implementing such a curriculum in three different countries—the Georgia, Israel, and the United States—as a means of identifying instructional barriers to implementation that may be hampering widespread adoption. Science is a discipline in which curriculum designers draw topics from a similar database. Teachers’ perception and practices could reflect global trends as well as the unique characteristics of each of the countries. Data for this qualitative study were collected from 15 high school science teachers in each of the three countries using semi-structured interviews. The findings indicate a gap between teachers’ desire and capacity to effectively implement an inquiry-based science curriculum. Common barriers to implementation mentioned by teachers in the three countries included a lack of time, official exams, and class size. Other country-specific reasons included lack of materials in the Georgian language or English language barriers in highly diverse classrooms in the United States. In order to make changes in the curriculum and create more opportunities for implementing an inquiry-based science curriculum, all obstacles identified by teachers should be taken into consideration. Potential interventions could include professional development, mentoring, and developing assessment tools for inquiry-based implementation

Automated segmentation of martensite-austenite islands in bainitic steel

So far, the qualitative and quantitative analysis of bainite has to be carried out by a metallography specialist and often causes ambiguities coming along with poor reproducibility. Possible reasons for a high variance in the description of bainite originate from different expert opinions given the high variety in the appearance of bainite in micrographs. In particular, the applied cooling regime and corresponding temperature gradients in the material dictate the evolving microstructure and its complexity. In recent years, deep learning showed its potential to provide a robust and fast quantification of image data derived from learning large datasets. In order to unfold the potential of deep learning and facilitate its usage for the material science community, a deeper understanding on the role of data pre-processing is necessary to capture the influence of metallography images (and their complexity) on the learning process. In this study, the open-source detection and segmentation library Detectron2 (https://github.com/facebookresearch/detectron2) was used within a framework to quantify a crucial constituent in bainite - the martensite-austenite (M-A) islands - in electron microscopy images. We provide three bainite data sets with image data representing different cooling regimes and therefore different M-A characteristics. From segmentation results, the ratio of constituent to image size manifests as a crucial parameter during pre-processing affecting the accuracy of subsequently trained models

Automated segmentation of martensite-austenite islands in bainitic steel

So far, the qualitative and quantitative analysis of bainite has to be carried out by a metallography specialist and often causes ambiguities coming along with poor reproducibility. Possible reasons for a high variance in the description of bainite originate from different expert opinions given the high variety in the appearance of bainite in micrographs. In particular, the applied cooling regime and corresponding temperature gradients in the material dictate the evolving microstructure and its complexity. In recent years, deep learning showed its potential to provide a robust and fast quantification of image data derived from learning large datasets. In order to unfold the potential of deep learning and facilitate its usage for the material science community, a deeper understanding on the role of data pre-processing is necessary to capture the influence of metallography images (and their complexity) on the learning process. In this study, the open-source detection and segmentation library Detectron2 (https://github.com/facebookresearch/detectron2) was used within a framework to quantify a crucial constituent in bainite - the martensite-austenite (M-A) islands - in electron microscopy images. We provide three bainite data sets with image data representing different cooling regimes and therefore different M-A characteristics. From segmentation results, the ratio of constituent to image size manifests as a crucial parameter during pre-processing affecting the accuracy of subsequently trained models

Disrupted Learning During COVID-19: A Survey of Student Experience

Navigating unexpected disruption caused by COVID-19 in Higher Education required immediate and flexible response by faculty and students as they pivoted to other learning modalities. In Spring Semester 2021, we administered a 40-question survey including several open-ended questions to 795 undergraduate and graduate students (master and doctoral level) in multiple disciplines across four Schools at a private university in Pennsylvania to capture student perceptions of learning experience in face-to-face, hybrid, and fully online environments. Ninety-nine students completed the survey. Lessons learned for teaching and learning include sensitivity to students’ stress and understanding learning environment design preferences and effectiveness