Teacher Scaffolding Strategies to Transform Whole-classroom Talk into Collective Inquiry in Elementary Science Classrooms

Inquiry-based teaching has been emphasized to enhance students’ knowledge and skills and create a culture of science in science classrooms. Many teachers understand inquiry as hands-on activities, and under the pressure of content-based curriculum, they plan hands-on activities to develop students’ science content knowledge described in the curriculum. This leads to science teaching as scripted performance-based teaching rather than creative and co-constructive knowledge building and problem solving. To develop inquiry abilities, students need opportunities to critically and constructively share and discuss their ideas, reasons, and alternatives in problem-solving contexts beyond managing experiments. Whole-classroom talk has been recognized as a cognitive and social tool to create a joint space of learning when teachers go beyond the traditional ground rules of the Initiation-Response-Follow-up/Initiation-Response-Evaluation (IRF/IRE) approach in classroom interactions. This study investigates examples of teacher scaffolding during whole-class discussion where an elementary teacher attempts to connect and expand hands-on activities with knowledge building, reasoning and problem-solving. This study examines specific scaffolding strategies used by the teacher during whole-class discussion and explores how the strategies develop a co-constructive learning community for students to enhance their knowledge, reasoning and problem-solving skills. The study employed a descriptive and explanatory case study model to look closely at a Grade 5-6 classroom over 4 months, with a specific focus on the dynamics of student and teacher interactions during classroom activities and discussions. During the course of the study, one teacher and 23 students worked on the science unit of electricity and electromagnetism. All science classes were video and audio taped and later transcribed to analyze the classroom talk, the teacher’s scaffolding strategies, and students’ learning. Research findings show that the teacher continuously demonstrated the strategies of a) probing and expanding the boundaries of thinking, b) developing collective reasoning and problem solving, and c) participating and modeling the inquiry process with students. These scaffolding strategies distributed the agency of reasoning and problem solving in a collective learning community and encouraged students to become knowledge inquirers and problem solvers. The study describes the pedagogical implications of whole-classroom talk through a discussion about how these strategies are related to and different from the widely practiced IRF/IRE approach in order for teachers to reflect and transform the practice of classroom talk into inquiry-based teaching. Keywords: Teacher scaffolding, collective inquiry, whole-classroom talk, elementary science On a favorisé l’apprentissage fondé sur l’enquête comme approche pour rehausser les connaissances et les habiletés des élèves et pour créer une culture de la science dans les cours de science. Plusieurs enseignants perçoivent l’enquête comme consistant en des activités pratiques et, sous la pression du curriculum basé sur le contenu, ils organisent des activités pratiques pour développer chez les élèves les connaissances en sciences selon le contenu décrit dans le programme d’étude. Cela mène à un enseignement des sciences qui est structuré et ancré dans la performance, plutôt qu’au développement créatif and collaboratif des connaissances et des capacités en résolution de problèmes. Afin de développer des compétences en enquête, les élèves ont besoin d’occasions de partager et de discuter, de façon critique et collaborative, leurs idées, leurs motifs et leurs solutions aux problèmes dans des contextes qui dépassent celui des expériences gérées. Les discussions impliquant la classe dans son ensemble sont reconnues comme étant un outil cognitif et social qui crée un espace d’apprentissage partagé quand les enseignants vont au-delà de l’approche traditionnelle d’initiation-réponse-suivi et initiation-réponse-évaluation pour gérer les interactions en classe. Cette étude se penche sur des exemples d’échafaudage pendant une discussion impliquant l’ensemble de la classe où un enseignant à l’élémentaire tente de faire le lien entre les activités pratiques d’une part et le développement des connaissances, de la capacité de raisonnement et des aptitudes en résolution de problèmes d’autre part. Cette étude examine des stratégies d’échafaudage spécifiques qu’emploient les enseignants pendant les discussions impliquant l’ensemble de la classe et explore la façon dont ces stratégies mènent au développement d’une communauté d’apprentissage collaborative où les élèves augmentent leurs connaissances, leur capacité de raisonnement et leurs habiletés en résolution de problèmes. L’étude repose sur un modèle d’étude de cas descriptive et explicative pour examiner une classe de 5e-6e pendant 4 mois, en portant surtout attention à la dynamique des interactions entre les élèves et l’enseignant pendant les activités et les discussions en classe. Au cours de l’étude, un enseignant et 23 élèves ont travaillé sur une unité en science portant sur l’électricité et l’électromagnétisme. Tous les cours de science ont été enregistrés sur bande vidéo et sonore et ensuite transcrits et analysés pour les conversations en classe, les stratégies d’échafaudage employées par l’enseignant et l’apprentissage des élèves. Les résultats de recherche indiquent que l’enseignant a constamment employé les stratégies suivantes: a) explorer et repousser les limites de la réflexion, b) développer la résolution de problèmes et le raisonnement collectifs, et c) montrer le processus d’enquête aux élèves et y participer. Ces stratégies d’échafaudage ont distribué les capacités de raisonnement et de résolution de problèmes dans une communauté d’apprentissage collectif et elles ont encouragé les élèves à devenir des chercheurs de connaissances et des personnes capables de résoudre des problèmes. L’étude décrit les retombées pédagogiques des discussions impliquant toute la classe et ce, en discutant des similarités et des différences entre les stratégies d’échafaudage et l’approche courante d’initiation-réponse-suivi et initiation-réponse-évaluation. Cette discussion se veut une invitation à la réflexion aux enseignants afin qu’ils transforment la pratique des discussions en classe en un enseignement reposant sur l’enquête. Mots clés : échafaudage par les enseignants, enquête collective, discussion impliquant toute la classe, science à l’élémentair

Two Works by Isang Yun and Byungdong Paik for Harpsichord or Piano: Analysis and Performance Guide

The harpsichord is no longer an instrument of the past. Since its revival in the nineteenth century, it has coexisted with the piano as one of the most important keyboard instruments. Modern composers all over the world have written music not only for the piano but also for the harpsichord. Composers and performers from non-Western countries have become interested in writing and playing music for the harpsichord. South Korean composers like Isang Yun and Byungdong Paik tend to mix their country’s musical style with Western compositional techniques. Yun’s Shao Yang Yin and Paik’s Three Bagatelles demonstrate the blending of Western modern compositional techniques with traditional Korean musical style. The harpsichord music by Yun and Paik show that the separation of old and new, traditional and modern, and Korean and Western is meaningless. Isang Yun’s Shao Yang Yin (1966) was intended from the start to be performed on either the harpsichord or the piano. The two contrasting characters from Taoist teaching – Yang and Yin – inspired Yun to create a mood and dynamics that change frequently. Yun uses a twelve-tone technique in this composition, as well as what he termed a “main-tone technique,” in which one note is decorated by surrounding notes and ornaments. Byungdong Paik composed his Three Bagatelles for the piano in 1973 and arranged it for the harpsichord fifteen years later, adding new sections of music in the first and second movements and an Intermezzo for improvisation between the second and third movements. Unlike Yun, Paik did not use twelve-tone technique in his Bagatelles, but instead focused on the basic musical elements of harmony, rhythm, and melody. He also uses a pivotal tone technique, in which a single note appears and is maintained until the end. Because both works can be performed either on the harpsichord or piano, different practice and performance approaches are required. Each instrument requires a different approach to the expression of dynamics and tone quality. Musical analysis of these two works helps the performer interpret the composer’s intention correctly before practice and performance. Performers should recognize the difference between the harpsichord and the piano, understand the strengths and weaknesses of their instrument, and strive to create the most effective and expressive sound on each. Thus, applying appropriate practice methods in accordance with musical context is essential to a successful performance

Web Applicable Computer-aided Diagnosis of Glaucoma Using Deep Learning

Glaucoma is a major eye disease, leading to vision loss in the absence of proper medical treatment. Current diagnosis of glaucoma is performed by ophthalmologists who are often analyzing several types of medical images generated by different types of medical equipment. Capturing and analyzing these medical images is labor-intensive and expensive. In this paper, we present a novel computational approach towards glaucoma diagnosis and localization, only making use of eye fundus images that are analyzed by state-of-the-art deep learning techniques. Specifically, our approach leverages Convolutional Neural Networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM) for glaucoma diagnosis and localization, respectively. Quantitative and qualitative results, as obtained for a small-sized dataset with no segmentation ground truth, demonstrate that the proposed approach is promising, for instance achieving an accuracy of 0.91$\pm0.02$ and an ROC-AUC score of 0.94 for the diagnosis task. Furthermore, we present a publicly available prototype web application that integrates our predictive model, with the goal of making effective glaucoma diagnosis available to a wide audience.Comment: Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:cs/010120

The effects of a group cognitive behavioral therapy program using video communication for pregnant women with depressed mood in Korea: a pilot study

Purpose This study presents the development of a group video communication-based cognitive behavioral therapy (CBT) program for depressed pregnant women. It also provides the results of a preliminary test of its effects on their depression, automatic thoughts, and dysfunctional attitudes. Methods In this quasi-experimental single-group pre- and posttest design study, 13 pregnant women participated in a 4-week, eight-session group CBT program, based on Beck’s cognitive theory and using video communications from November 2020 to January. Pregnant women between 14 and 32 weeks who were members of an online maternity and parenting community and residing in the cities of Changwon and Gimhae, Korea, were invited to voluntarily participate. Trained nurses led CBT sessions of 3–4 participants per group via video communication. Participants were assessed pre- and postintervention with self-report questionnaires for measurement of depression, automatic thought, and dysfunctional attitude after normality test according to the Shapiro-Wilk test of the variables. The data were analyzed using paired t-test and Pearson correlation coefficients. Results Depression (t=7.90, p<.001), automatic thoughts (t=4.89, p<.001), and dysfunctional attitudes (t=2.42, p=.032) significantly decreased after the 4-week online program. There were statistically significant correlations among the three variables. Conclusion This program was found to be effective in reducing depression, automatic thoughts, and dysfunctional attitudes. Above findings suggest that a group CBT program using video communication can be an effective therapeutic modality that helps pregnant women at risk for depression alleviate their negative emotions related to depression

The experiences of depressed pregnant women participating in a cognitive behavioral therapy program via video communication: an exploratory qualitative study

Purpose This study explored the experiences of pregnant women with depressed mood participating in a group cognitive behavioral therapy (CBT) program using video communication, based on Beck’s cognitive theory. Methods The participants were six pregnant women out of 13 women who had participated in an 8-session group CBT program using video communication for women with depressed mood (Edinburgh Postnatal Depression score of ≥9). Data were collected from February 20 through March 25, 2021. In-depth individual interviews were conducted through a video conferencing platform at 1 month post-baseline. Thematic analysis was done. Results Three themes, 10 subthemes, and 38 concepts were derived from experiences of participating in the 4-week group CBT program (twice a week). The first theme, entitled “continuing realization” had subthemes of “a negative and instable self,” “a selfish judgment that excludes others,” and “a strong belief in self-control.” The second theme, entitled “attempt to change for restoration” had subthemes of “shift to rational thinking,” “freedom from suppressed beliefs,” “tolerance of other people,” and “courage for self-expression.” The third theme, entitled “departure for a positive life,” had subthemes of “emotional healing,” “faith in oneself,” and “reestablishing the criteria for happiness.” Conclusion Pregnant women with depressed mood expressed that continuing realizations and attempts to change supported their transition toward a positive direction of healing. Thus, they were able to change their distorted thinking into rational thinking through CBT using video communication. These findings support the use of group CBT using video communication with pregnant women who have depressed mood

Awareness, Discovery, Becoming, and Debriefing: Promoting Cross-Cultural Pedagogical Understanding in an Undergraduate Education Program

This article discusses the first phase of an action research project aimed at identifying a collaborative and collective response to the need to prepare student teachers to work in diverse school contexts. The research brought together university researchers, community and cultural institutions, professional associations, school boards, and government and civil organizations to design a Diversity Institute for integration into the teacher preparation program at the University of Alberta. Student teachers’ responses to the Diversity Institute suggest that although a few participants were able to develop new understandings of themselves and others and to effect changes in their pedagogical practices, many remained at a shallow level of awareness about the complexities of diversity and difference. Reflections on the first phase of the Institute point to the underlying dynamics of learning and unlearning that are at work in becoming a teacher and the need for time and space for a deeper engagement with diversity in the teacher education program.Cet article présente la première phase d’un projet de recherche action visant l’identification d’une réponse collaborative et collective au besoin de préparer les étudiants en pédagogie à travailler dans divers contextes scolaires. La recherche a impliqué la collaboration de chercheurs universitaires, d’instituts communautaires et culturels, d’associations professionnelles, de conseils scolaires et d’organisations gouvernementales et civiles, dans la conception d’une série d’ateliers et de présentations (nommée Diversity Institute 2008) qui a ensuite été intégrée au programme de pédagogie à l’Université de l’Alberta. La réaction des étudiants en pédagogie qui ont participé aux ateliers et aux présentations indique que, même si quelques participants ont pu développer de nouvelles connaissances sur eux-mêmes et les autres, et qu’ils ont réussi à modifier leurs pratiques pédagogiques, plusieurs n’ont acquis qu’une connaissance superficielle des complexités de la diversité et la différence. Les réflexions sur la première phase de Diversity Institute ont fait ressortir, d’une part, les rapports dynamiques et sous-jacents d’apprentissage et de désapprentissage qui accompagnent la formation des étudiants en pédagogie et, d’autre part, le besoin de temps et d’espace au sein du programme de pédagogie pour permettre une appréciation approfondie de la diversité

Microscopic observation of a liquid-liquid-(semi)solid phase in polluted PM2.5

Atmospheric aerosol particles are complex mixtures having various physicochemical properties. To predict the role and characteristics of such complex aerosol particles in air pollution and related atmospheric chemistry, our knowledge of the number and types of phases in complex aerosol particles should be improved. However, most studies on the phase behavior of aerosol particles have been conducted in the laboratory and have not used real-world aerosol particles. In this study, using a combination of optical microscopy and poke-and-flow technique, we investigated the number and types of phases of actual aerosol particles of particulate matter &lt; 2.5 µm (PM2.5) collected on heavily polluted days in Seosan, South Korea in winter 2020–2021. From the microscopic observations at 293 K, it showed that the PM2.5 particles exist in a single liquid phase at relative humidity (RH) &gt;∼85%, a liquid-liquid phase at ∼70% &lt; RH &lt;∼85%, a liquid-liquid-(semi)solid phase at ∼30% &lt; RH &lt;∼70%, and a (semi)solid phase at RH &lt;∼30% upon dehydration. This reveals that three phases of atmospheric aerosol particles coexisting as liquid-liquid and liquid-liquid-(semi)solid would be the most common phases in the atmosphere considering ambient RH ranges. These observations provide fundamental properties necessary for improved predictions of air quality and aerosol chemistry such as reactive uptake of N2O5, size distributions, and mass concentrations of aerosol particles

Impact of Large Language Models on Generating Software Specifications

Software specifications are essential for ensuring the reliability of software systems. Existing specification extraction approaches, however, suffer from limited generalizability and require manual efforts. We study the effectiveness of Large Language Models (LLMs) in generating software specifications from software documentation, utilizing Few-Shot Learning (FSL) to enable LLMs to generalize from a small number of examples. We compare the performance of LLMs with FSL to that of state-of-the-art specification extraction techniques and study the impact of prompt construction strategies on LLM performance. In addition, we conduct a comprehensive analysis of their symptoms and root causes of the failures to understand the pros and cons of LLMs and existing approaches. We also compare 11 LLMs' performance, cost, and response time for generating software specifications. Our findings include that (1) the best performing LLM outperforms existing approaches by 9.1--13.7% with a few similar examples, (2) the two dominant root causes combined (ineffective prompts and missing domain knowledge) result in 57--60% of LLM failures, and (3) most of the 11 LLMs achieve better or comparable performance compared to traditional techniques. Our study offers valuable insights for future research to improve specification generation

Medinoid : computer-aided diagnosis and localization of glaucoma using deep learning

Glaucoma is a leading eye disease, causing vision loss by gradually affecting peripheral vision if left untreated. Current diagnosis of glaucoma is performed by ophthalmologists, human experts who typically need to analyze different types of medical images generated by different types of medical equipment: fundus, Retinal Nerve Fiber Layer (RNFL), Optical Coherence Tomography (OCT) disc, OCT macula, perimetry, and/or perimetry deviation. Capturing and analyzing these medical images is labor intensive and time consuming. In this paper, we present a novel approach for glaucoma diagnosis and localization, only relying on fundus images that are analyzed by making use of state-of-the-art deep learning techniques. Specifically, our approach towards glaucoma diagnosis and localization leverages Convolutional Neural Networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM), respectively. We built and evaluated different predictive models using a large set of fundus images, collected and labeled by ophthalmologists at Samsung Medical Center (SMC). Our experimental results demonstrate that our most effective predictive model is able to achieve a high diagnosis accuracy of 96%, as well as a high sensitivity of 96% and a high specificity of 100% for Dataset-Optic Disc (OD), a set of center-cropped fundus images highlighting the optic disc. Furthermore, we present Medinoid, a publicly-available prototype web application for computer-aided diagnosis and localization of glaucoma, integrating our most effective predictive model in its back-end