Attention as Annotation: Generating Images and Pseudo-masks for Weakly Supervised Semantic Segmentation with Diffusion

Although recent advancements in diffusion models enabled high-fidelity and diverse image generation, training of discriminative models largely depends on collections of massive real images and their manual annotation. Here, we present a training method for semantic segmentation that neither relies on real images nor manual annotation. The proposed method {\it attn2mask} utilizes images generated by a text-to-image diffusion model in combination with its internal text-to-image cross-attention as supervisory pseudo-masks. Since the text-to-image generator is trained with image-caption pairs but without pixel-wise labels, attn2mask can be regarded as a weakly supervised segmentation method overall. Experiments show that attn2mask achieves promising results in PASCAL VOC for not using real training data for segmentation at all, and it is also useful to scale up segmentation to a more-class scenario, i.e., ImageNet segmentation. It also shows adaptation ability with LoRA-based fine-tuning, which enables the transfer to a distant domain i.e., Cityscapes

A program evaluation of a CLIL course at IED Sofía Camargo de Lleras

Content and Language Integrated Language Learning (CLIL) is considered as a dual focused methodology in which a second or foreign language is used as a medium in the teaching and learning of content. The syllabus and programs designed focusing on the CLIL of frameworks have their objectives articulated with goals and outcomes for teaching and learning. There has been evidence that a curriculum based upon content and topics rather than language functions and structure is efficacious in helping students develop their English in a significant and stimulating manner. In 2010, in the IED Sofia Camargo de Lleras, a public school for girls located in Barranquilla, Colombia, there was a curriculum evaluation process that determined that the English curriculum was articulated nor with the Institution`s vision or students’ needs. For instance, in the EFL classrooms, students’ declarative knowledge enabled them describe a rule of grammar and apply it in pattern practice drills and not in meaningful context of use. Worrying about this situation, actions started to be taken to face it. In 2012, a needs analysis was conducted to 10th graders. The results obtained from the data collected called for a Content and Language Integrated language program dealing with those contents that students study in their Personal Development classes. A Content Based pilot course was designed and implemented. The methodological strategies for the design and implementation were the ones proposed by Marsh (2006), Ball (2010), O’Malley & Chamot (1999) and Levelt (1993). To analyze the program’s coherence and effectiveness, it was necessary to move to the field of evaluation research using qualitative methods to collect and analyze the data (Stufflebeam & Shinkfiel, 2007).MaestríaMagister en la Enseñanza del Ingle

Cooperative learning in CLIL history lessons

Diese Doktorarbeit bezieht sich auf die kooperativen Lernmethoden im CLIL Geschichtsunterricht. Die Arbeit beinhaltet die folgenden wichtigen Aspekte. Zuerst ist theoretische und empirische Untersuchung durchgeführt worden, um herauszufinden, inwieweit kooperative Lernmethoden in CLIL (Integriertes Fremdsprachen- und Sachfachlernen) Geschichtsunterricht integriert sind. Außerdem sind die Rolle der Lehrer und deren Interventionsfrequenz im kooperativen Unterricht untersucht worden. Zweitens ist der Einfluss von kooperativen Lernmethoden auf die Motivation der Schüler im CLIL Geschichtsunterricht erforscht worden, wobei der Fokus auf der Gruppenheterogenität, Peer-Interaktion und Autonomie der Lernenden liegt. Drittens ist der Einfluss von kooperativen Lernmethoden auf die Fremdsprachenkenntnisse, Fachkenntnisse und nicht-akademische Fähigkeiten der Schüler im CLIL Geschichtsunterricht untersucht worden. Zur Ausführung dieser Forschung wurden sechs Lehrer*innen aus fünf verschiedenen Schulen in Berlin interviewt

SeiT: Storage-Efficient Vision Training with Tokens Using 1% of Pixel Storage

We need billion-scale images to achieve more generalizable and ground-breaking vision models, as well as massive dataset storage to ship the images (e.g., the LAION-4B dataset needs 240TB storage space). However, it has become challenging to deal with unlimited dataset storage with limited storage infrastructure. A number of storage-efficient training methods have been proposed to tackle the problem, but they are rarely scalable or suffer from severe damage to performance. In this paper, we propose a storage-efficient training strategy for vision classifiers for large-scale datasets (e.g., ImageNet) that only uses 1024 tokens per instance without using the raw level pixels; our token storage only needs <1% of the original JPEG-compressed raw pixels. We also propose token augmentations and a Stem-adaptor module to make our approach able to use the same architecture as pixel-based approaches with only minimal modifications on the stem layer and the carefully tuned optimization settings. Our experimental results on ImageNet-1k show that our method significantly outperforms other storage-efficient training methods with a large gap. We further show the effectiveness of our method in other practical scenarios, storage-efficient pre-training, and continual learning. Code is available at https://github.com/naver-ai/seitComment: ICCV 2023; First two authors contributed equally; code url: https://github.com/naver-ai/seit; 17 pages, 1.2M

My brain wakes up

An original work of fiction designed to open the conversation between students and teachers about the striking contrasts and innate beauty in how differently each of our brains are made. It is at once a work of fiction, an interview of children, an opportunity for personal reflection, and an invitation for all learners to honor our unique creativity

Coreset Selection with Prioritized Multiple Objectives

Coreset selection is powerful in reducing computational costs and accelerating data processing for deep learning algorithms. It strives to identify a small subset from large-scale data, so that training only on the subset practically performs on par with full data. When coreset selection is applied in realistic scenes, under the premise that the identified coreset has achieved comparable model performance, practitioners regularly desire the identified coreset can have a size as small as possible for lower costs and greater acceleration. Motivated by this desideratum, for the first time, we pose the problem of "coreset selection with prioritized multiple objectives", in which the smallest coreset size under model performance constraints is explored. Moreover, to address this problem, an innovative method is proposed, which maintains optimization priority order over the model performance and coreset size, and efficiently optimizes them in the coreset selection procedure. Theoretically, we provide the convergence guarantee of the proposed method. Empirically, extensive experiments confirm its superiority compared with previous strategies, often yielding better model performance with smaller coreset sizes

Pragmatics in Game Activities, Humor, and Technology in Second Language Learning

This portfolio compiles work the author explored and developed during the Master of Second Language Teaching (MSLT) program at Utah State University (USU). It encompasses a range of experiences from teaching abroad and at USU, insights from the observation of other classrooms, and reflections from studies in the MSLT program. Three distinct sections comprise the portfolio: teaching perspectives, research perspectives, and an annotated bibliography. The teaching perspectives detail beliefs regarding games, computer technology, humor, and pragmatics and how they influence second language learning based on the author’s personal experiences. The research perspectives and annotated bibliography elaborate further on those topics by investigating related research findings

The classroom implementation of indigenous knowledge in the science curriculum by science teachers in the Western Cape province, South Africa

Includes bibliographical referencesThe South African policy document of the Revised National Curriculum Statement (RNCS) for Natural Science (Department of Education, 2002), the National Curriculum Statement (NCS) for Life Science (Department of Education, 2003), and the Curriculum and Assessment Policy Statement (CAPS) for Natural Science and Life Science (Department of Education, 2011) recognises and affirms the critical role of Indigenous Knowledge Systems (IKS) in science education. These policy documents expect the science teachers to integrate indigenous knowledge in their lessons. This study strove to establish how selected high school science teachers in the Western Cape Province responded to the inclusion of indigenous knowledge in their teaching. The present study employed a multi-method approach, involving different research methods used in parallel or sequence but are not integrated until inferences are made (Johnson, Onwuegbuzie & Turner, 2007). This study took place in two main sequential data collection phases, namely, the quantitative data collection phase ((QUAN) and the qualitative data collection phase (qual). This contemporary approach was employed in order to provide credible and trustworthy answers to the following research questions, namely, 1) To what extent are the science teachers in the Western Cape Province integrating scientific and indigenous knowledge, as required by the Department of Education? If not, what are their reasons for this? 2) What are the teachers' views about and understanding of the nature of science and indigenous knowledge as well as their views on how the two worldviews can be integrated in the classroom? 3) How effective was the treatment in enhancing the teachers' ability to integrate science and indigenous knowledge in the classroom? 4) To what extent can the model of Snively and Corsiglia (2001) be useful for measuring change as the teachers implement the integration of indigenous knowledge in the science classroom? For the QUAN phase, the researcher adapted a questionnaire and a new questionnaire, the Nature of Indigenous Knowledge Questionnaire (NOIKQ), was developed. The purpose of this questionnaire was to obtain a detailed description of high schools science teachers' understanding of scientific and indigenous knowledge, as well as the problems the teachers encounter in their implementation of Learning Outcome 3 of Life Sciences and Natural Science. After the pilot study of the questionnaire and subsequent modifications to it, data were collected. Convenience sampling and purposeful sampling characterised the samples of respondents and schools. This sampling strategy ensured a total sample of 370 high school science teachers in 80 public schools, represented by urban and township schools in the Western Cape Province. The results of the QUAN phase indicated that the teachers did not receive training on how to integrate science and indigenous knowledge, and that they did not have sufficient knowledge of indigenous knowledge to teach this aspect confidently to their learners. An inquiry was embarked on in order to train the science teachers in how to integrate indigenous knowledge in the science classrooms. A workshop was chosen as an intervention to improve the teaching skills of the teachers and to develop new methods of teaching. A quasi-experimental design was chosen to establish how effective the intervention was. In this quasi-experimental design, one group of five teachers was assigned to the intervention, whilst the other group of six teachers received no intervention at all. This intervention was based on the model of Snively and Corsiglia (2001) for integrating IK in the science curriculum. These teachers had participated in the survey and were selected for their particular interest in the research study. Classroom observations and three teacher and six learner interviews were used for collecting qualitative data to establish the effectiveness of the intervention. A finding from this study is that the worldviews that the teachers bring into the classroom have implications for approaches they take to include IKS in their lessons. The results of the qualitative phase indicated that, given the teachers background (i.e., cultural, political and social), teachers interpreted and implemented IKS in different ways in the curriculum. The teachers who attended the workshop and were trained to integrate indigenous knowledge in the science curriculum were more confident than those teachers who were not trained to integrate IK in the science curriculum. This increased confidence resulted from the workshop which enhanced the teachers' IK content knowledge and made them less dependent on the learners for examples of IKS. The study offers important implications and recommendations to teachers and policy- makers regarding the implementation of the integration of IKS in the science curriculum, as well as fruitful avenues for further research