Papers by Carlos LopezLeiva
Relational engagement: Proportional reasoning with bilingual Latino/a students
Educational Studies in Mathematics, Aug 1, 2013
ABSTRACT In this paper, we explored how engagement developed over time during a proportional reas... more ABSTRACT In this paper, we explored how engagement developed over time during a proportional reasoning unit for a group of US bilingual Latino/a students, with particular attention to aspects of social and cultural activity that supported students’ engagement. Our findings suggest that student mathematical engagement developed primarily as a relational process characterized by students’ social relations across time, their understandings about their relationships with mathematics, and the important relations emerging across proportional reasoning ideas.
Acknowledging Spanish and English resources during mathematical reasoning
Cultural Studies of Science Education, Aug 28, 2013
ABSTRACT As English-only efforts continue in the US schooling system, dual-language programs have... more ABSTRACT As English-only efforts continue in the US schooling system, dual-language programs have served as attempts to preserve students' home language. An after-school, dual-language, Spanish-English, mathematics program, Los Rayos was developed in a predominantly Mexican/Mexican-American neighborhood in Chicago. As participant observers with a sociocultural perspective, we explored the linguistic and personal resources used by participating 4th grade bilingual Latina/o students. We found that students used imaginative, playful, and hybrid linguistic resources to make sense of and solve probability tasks when engaged within a zone of mathematical practice. Results challenge narrow perspectives on bilingual students' linguistic resources. Language implications are discussed.
Learning about community through mathematics: Mathematizing slopes
Este articulo presentat un enfoque conceptual usando un enfoque de ethnomodelaje para explorar, i... more Este articulo presentat un enfoque conceptual usando un enfoque de ethnomodelaje para explorar, introducir, y aprender el concepto de pendiente. La relevancia historica y cultural de sitios comunales son reslatdos como procesos que promueven acceso a la compresion y razonamiento del estudio contextualizado de la pendiente. Ideas sobre posibles aplicaciones son mencionadas.
“Juntos pero no revueltos”: microaggressions and language in the mathematics education of non-dominant Latinas/os
Mathematics Education Research Journal, Jan 5, 2014
ABSTRACT In this paper, we discuss the characteristics of microaggressions based on minority lang... more ABSTRACT In this paper, we discuss the characteristics of microaggressions based on minority language(s) as a form of discriminatory practice against non-dominant students in the mathematics context. Microaggressions are subtle, brief, and commonplace verbal, behavioral, or visual negative slights or insults toward people of color. We extend the concept of microaggression to include discrimination based on a minority language. We draw on our work with Latinas/os in the USA to demonstrate the occurrence of microaggressions in the teaching act. Revealing microaggressions based on language has the potential of creating more equitable learning environments for non-dominant students and can point to possible directions for future research and improvements in the preparation of teachers who serve non-dominant students who speak a language other than the school’s official language.
A Participatory Turn in Mathematics Education Research: Possibilities and Tensions
Journal for Research in Mathematics Education, May 1, 2023
Mathematics education researchers concerned with justice and rehumanizing mathematics education a... more Mathematics education researchers concerned with justice and rehumanizing mathematics education are increasingly calling for research that takes seriously the values, commitments, and voices of the communities for which the research is most consequential. Exclusion of or superficial engagement with these perspectives and experiences in research and design processes have perpetuated deficit perspectives of minoritized communities, rendering them simply the object of reform efforts. Consequently, this Research Commentary conceptualizes a participatory turn in mathematics education research, offering a set of commitments that guide and examine the possibilities and tensions of such a turn.
Valuing Indigenous Mathematical Knowledge: Collaborating With Guatemalan Teachers for the Instruction of Mesoamerican Numbers (Poster 36)
AERA 2022
2021 55th Asilomar Conference on Signals, Systems, and Computers, 2021
We introduce the problem of detecting a group of students from classroom videos. The problem requ... more We introduce the problem of detecting a group of students from classroom videos. The problem requires the detection of students from different angles and the separation of the group from other groups in long videos (one to one and a half hours). We use multiple image representations to solve the problem. We use FM components to separate each group from background groups, AM-FM components for detecting the back-of-the-head, and YOLO for face detection. We use classroom videos from four different groups to validate our approach. Our use of multiple representations is shown to be significantly more accurate than the use of YOLO alone.
Long-term Human Video Activity Quantification of Student Participation
2021 55th Asilomar Conference on Signals, Systems, and Computers, 2021
Research on video activity recognition has been primarily focused on differentiating among many d... more Research on video activity recognition has been primarily focused on differentiating among many diverse activities defined using short video clips. In this paper, we introduce the problem of reliable video activity recognition over long videos to quantify student participation in collaborative learning environments (45 minutes to 2 hours).Video activity recognition in collaborative learning environments contains several unique challenges. We introduce participation maps that identify how and when each student performs each activity to quantify student participation. We present a family of low-parameter 3D ConvNet architectures to detect these activities. We then apply spatial clustering to identify each participant and generate student participation maps using the resulting detections.We demonstrate the effectiveness by training over about 1,000 3-second samples of typing and writing and test our results over ten video sessions of about 10 hours. In terms of activity detection, our methods achieve 80% accuracy for writing and typing that match the recognition performance of TSN, SlowFast, Slowonly, and I3D trained over the same dataset while using 1200x to 1500x fewer parameters. Beyond traditional video activity recognition methods, our video activity participation maps identify how each student participates within each group.
2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), 2018
The paper introduces the problem of robust head detection in collaborative learning environments.... more The paper introduces the problem of robust head detection in collaborative learning environments. In such environments, the camera remains fixed while the students are allowed to sit at different parts of a table. Example challenges include the fact that students may be facing away from the camera or exposing different parts of their face to the camera. To address these issues, the paper proposes the development of two new methods based on Amplitude Modulation-Frequency Modulation (AM-FM) models. First, a combined approach based on color and FM texture is developed for robust face detection. Secondly, a combined approach based on processing the AM and FM components is developed for robust, back of the head detection. The results of the two approaches are also combined to detect all of the students sitting at each table. The robust face detector achieved 79% accuracy on a set of 1000 face image examples. The back of the head detector achieved 91% accuracy on a set of 363 test image examples.
2018 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), 2018
Human activity classification remains challenging due to the strong need to eliminate structural ... more Human activity classification remains challenging due to the strong need to eliminate structural noise, the multitude of possible activities, and the strong variations in video acquisition. The current paper explores the study of human activity classification in a collaborative learning environment. This paper explores the use of color based object detection in conjunction with contextualization of object interaction to isolate motion vectors specific to each human activity. The basic approach is to make use of separate classifiers for each activity. Here, we consider the detection of typing, writing, and talking activities in raw videos. The method was tested using 43 uncropped video clips with 620 video frames for writing, 1050 for typing, and 1755 frames for talking. Using simple KNN classifiers, the method gave accuracies of 72.6% for writing, 71% for typing and 84.6% for talking. Classification accuracy improved to 92.5% (writing), 82.5% (typing) and 99.7% (talking) with the use of Deep Neural Networks.
Computer Analysis of Images and Patterns, 2021
We study the problem of detecting talking activities in collaborative learning videos. Our approa... more We study the problem of detecting talking activities in collaborative learning videos. Our approach uses head detection and projections of the log-magnitude of optical flow vectors to reduce the problem to a simple classification of small projection images without the need for training complex, 3-D activity classification systems. The small projection images are then easily classified using a simple majority vote of standard classifiers. For talking detection, our proposed approach is shown to significantly outperform single activity systems. We have an overall accuracy of 59% compared to 42% for Temporal Segment Network (TSN) and 45% for Convolutional 3D (C3D). In addition, our method is able to detect multiple talking instances from multiple speakers, while also detecting the speakers themselves.
Computer Analysis of Images and Patterns, 2021
Speech recognition is very challenging in student learning environments that are characterized by... more Speech recognition is very challenging in student learning environments that are characterized by significant cross-talk and background noise. To address this problem, we present a bilingual speech recognition system that uses an interactive video analysis system to estimate the 3D speaker geometry for realistic audio simulations. We demonstrate the use of our system in generating a complex audio dataset that contains significant cross-talk and background noise that approximate real-life classroom recordings. We then test our proposed system with real-life recordings. In terms of the distance of the speakers from the microphone, our interactive video analysis system obtained a better average error rate of 10.83% compared to 33.12% for a baseline approach. Our proposed system gave an accuracy of 27.92% that is 1.5% better than Google Speech-to-text on the same dataset. In terms of 9 important keywords, our approach gave an average sensitivity of 38% compared to 24% for Google Speechto-text, while both methods maintained high average specificity of 90% and 92%. On average, sensitivity improved from 24% to 38% for our proposed approach. On the other hand, specificity remained high for both methods (90% to 92%).
Computer Analysis of Images and Patterns, 2021
Face recognition in collaborative learning videos presents many challenges. In collaborative lear... more Face recognition in collaborative learning videos presents many challenges. In collaborative learning videos, students sit around a typical table at different positions to the recording camera, come and go, move around, get partially or fully occluded. Furthermore, the videos tend to be very long, requiring the development of fast and accurate methods. We develop a dynamic system of recognizing participants in collaborative learning systems. We address occlusion and recognition failures by using past information about the face detection history. We address the need for detecting faces from different poses and the need for speed by associating each participant with a collection of prototype faces computed through sampling or K-means clustering. Our results show that the proposed system is proven to be very fast and accurate. We also compare our system against a baseline system that uses InsightFace [2] and the original training video segments. We achieved an average accuracy of 86.2% compared to 70.8% for the baseline system. On average, our recognition rate was 28.1 times faster than the baseline system.
2016 50th Asilomar Conference on Signals, Systems and Computers, 2016
The paper proposes an open-source, maintainable system for detecting human activity in video data... more The paper proposes an open-source, maintainable system for detecting human activity in video datasets using scalable hardware architectures. The system is validated by detecting writing and typing activities that were collected as part of the Advancing Out of School Learning in Mathematics and Engineering (AOLME) project. The implementation of the system using Amazon Web Services (AWS) is shown to be both horizontally and vertically scalable. The software associated with the system was designed to be robust so as to facilitate reproducibility and extensibility for future research.
Digital Video Representations for Teaching Mathematics and Coding to Middle School Students
2023 24th International Conference on Digital Signal Processing (DSP)
Promoting Equitable Systems in Mathematics Education Starts with Us: Linking Literature on Allywork to the Work of Mathematics Teacher Educators
Research in mathematics education, 2018
Mathematics teacher educators (MTEs) within mathematics education systems have unearned assets th... more Mathematics teacher educators (MTEs) within mathematics education systems have unearned assets that present strengths and challenges to the process of developing relationships with mathematics teachers (MTs), students, and their communities. Aware of such issues, we discuss in this chapter the concept and potential applications of allywork for the promotion of equitable systems in mathematics education. With this goal, we draw on literature from within and outside of mathematics education to (1) understand sociohistorical reasons for why MTEs should consider an ally stance in their work with MTs, (2) to consider who an ally is (and is not), and (3) to detail what allywork entails. An analysis of the coercive and hierarchical relations that the mathematics education field has inherited through the systemic feminization of education in the classroom and the masculinization of research and teacher education and the current diverse demographics of the US mathematics educational system frames the need and relevance of allywork. Allywork is understood as MTEs and MTs (as well as students and their community) working with each other in self, others, and systems (SOS) spaces. Description of an interior as well as exterior negotiation and disruption of issues of privilege and oppression highlight the personal and yet systemic dimensions required in MTEs’ work and identities as allies. This chapter further contrasts allywork with other stances, links these ideas to mathematics education, and raises questions on how MTEs’ work and identities critically address and intersect with the goals, needs, and actions of others in SOS spaces.
Entre Hilos, Colmillos, y Monstruos : Newcomer Latinx Bilingual Students Learning Computer Programming Through Translanguaging
AERA 2022
“Fake It Until You Make It”: Participation and Positioning of a Bilingual Latina Student in Mathematics and Computing
Teachers College Record: The Voice of Scholarship in Education
Background/Context: After-school programs that focus on integrating computer programming and math... more Background/Context: After-school programs that focus on integrating computer programming and mathematics in authentic environments are seldomly accessible to students from culturally and linguistically diverse backgrounds, particularly bilingual Latina students in rural contexts. Providing a context that broadens Latina students’ participation in mathematics and computer programming requires educators to carefully examine how verbal and nonverbal language is used to interact and to position students as they learn new concepts in middle school. This is also an important stage for adolescents because they are likely to make decisions about their future careers in STEM. Having access to discourse and teaching practices that invite students to participate in mathematics and computer programming affords them opportunities to engage with these fields. Purpose/Focus of Study: This case study analyzes how small-group interactions mediated the positionings of Cindy, a bilingual Latina, as sh...
Teaching and Learning Mathematics and Computing in Multilingual Contexts
Teachers College Record: The Voice of Scholarship in Education
A educação enquanto fenômeno social: Avanços, limites e contradições 4
Direitos para esta edição cedidos à Atena Editora pelos autores. Open access publication by Atena... more Direitos para esta edição cedidos à Atena Editora pelos autores. Open access publication by Atena Editora Todo o conteúdo deste livro está licenciado sob uma Licença de Atribuição Creative Commons. Atribuição-Não-Comercial-NãoDerivativos 4.0 Internacional (CC BY-NC-ND 4.0). O conteúdo dos artigos e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos autores, inclusive não representam necessariamente a posição oficial da Atena Editora. Permitido o download da obra e o compartilhamento desde que sejam atribuídos créditos aos autores, mas sem a possibilidade de alterá-la de nenhuma forma ou utilizá-la para fins comerciais. Todos os manuscritos foram previamente submetidos à avaliação cega pelos pares, membros do Conselho Editorial desta Editora, tendo sido aprovados para a publicação com base em critérios de neutralidade e imparcialidade acadêmica. A Atena Editora é comprometida em garantir a integridade editorial em todas as etapas do processo de publicação, evitando plágio, dados ou resultados fraudulentos e impedindo que interesses financeiros comprometam os padrões éticos da publicação. Situações suspeitas de má conduta científica serão investigadas sob o mais alto padrão de rigor acadêmico e ético.
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Papers by Carlos LopezLeiva