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Carlos LopezLeiva
University of New Mexico
Collaborative learningSociologyMathematics educationPedagogyComputer science
15Publications
2H-index
26Citations
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Publications 16
Newest
#1Rebecca M. Sánchez (UNM: University of New Mexico)H-Index: 3
#2Karla V. Kingsley (UNM: University of New Mexico)H-Index: 4
Last. Hollie Putnam (UNM: University of New Mexico)
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#1Carlos LopezLeiva (UNM: University of New Mexico)H-Index: 2
#2Eugenia Vomvoridi-Ivanovic (USF: University of South Florida)H-Index: 4
Last. Craig J. Willey (IU: Indiana University)
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ABSTRACTThe preparation of bilingual prospective teachers (BPTs) in mathematics encompasses a challenge because many U.S.-born BPTs had limited opportunities to learn mathematics in their native la...
1 CitationsSource
#1Carlos LopezLeiva (UNM: University of New Mexico)H-Index: 2
#2Marios S. Pattichis (UNM: University of New Mexico)H-Index: 26
Last. Sylvia Celedón-Pattichis (UNM: University of New Mexico)H-Index: 5
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Whilst Science, Technology, Engineering and Mathematics (STEM) interdisciplinary teaching and learning in the USA K-12 education still needs greater promotion, middle school students demonstrated that they can, using low-cost, single board computers that promote the teaching of computer science (in this case Raspberry Pis), successfully engage with computer programming of digital images and videos. The context for these students’ engagement was the Advancing Out-of-School Learning in Mathematics...
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#1Wenjing Shi (UNM: University of New Mexico)
#2Marios S. Pattichis (UNM: University of New Mexico)H-Index: 26
Last. Carlos LopezLeiva (UNM: University of New Mexico)H-Index: 2
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We introduce a new method to detect student group interactions in collaborative learning videos. We consider the following video activities: (i) human to human, (ii) human to others, and (iii) lack of any interaction. The system uses multidimensional AM-FM methods to detect student faces, hair, and then use the results to detect possible interactions. We use dynamic graphs to represent group interactions within each video. We tested our methods with 15 videos and achieved an 84% accuracy for stu...
1 CitationsSource
#1Wenjing Shi (UNM: University of New Mexico)
#2Marios S. Pattichis (UNM: University of New Mexico)H-Index: 26
Last. Carlos LopezLeiva (UNM: University of New Mexico)H-Index: 2
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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...
1 CitationsSource
#1Abigail Ruth Jacoby (UNM: University of New Mexico)H-Index: 1
#2Marios S. Pattichis (UNM: University of New Mexico)H-Index: 26
Last. Carlos LopezLeiva (UNM: University of New Mexico)H-Index: 2
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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...
1 CitationsSource
#1Carlos LopezLeiva (UNM: University of New Mexico)H-Index: 2
#2Beth Herbel-Eisemann (MSU: Michigan State University)
Last. Ayşe Yolcu (Hacettepe University)H-Index: 1
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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)...
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Mar 5, 2017 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Marios S. Pattichis (UNM: University of New Mexico)H-Index: 26
#2Sylvia Celedón-Pattichis (UNM: University of New Mexico)H-Index: 5
Last. Carlos LopezLeiva (UNM: University of New Mexico)H-Index: 2
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In this paper, we summarize some of the lessons learned from the Advancing Out-of-School Learning in Mathematics and Engineering (AOLME) project. The AOLME project uses an integrated curriculum that relies on the use of basic concepts from middle-school mathematics to teach the foundations of image and video representations. The middle-school students, mostly from underrepresented groups, learn how to program their own video representations using Python libraries running on the Raspberry Pi. Ove...
2 CitationsSource
Nov 1, 2016 in ASILOMAR (Asilomar Conference on Signals, Systems and Computers)
#1Cody W. Eilar (UNM: University of New Mexico)H-Index: 1
#2Venkatesh Jatla (UNM: University of New Mexico)H-Index: 1
Last. Sylvia Celedón-Pattichis (UNM: University of New Mexico)H-Index: 5
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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 ...
2 CitationsSource
#1Carlos LopezLeiva (UNM: University of New Mexico)H-Index: 2
#2Deborah Roberts-Harris (UNM: University of New Mexico)H-Index: 1
Last. Elizabeth von TollH-Index: 1
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Through a collaborative effort between a sixth-grade teacher and two university faculty, we designed an integrated unit to learn about motion and we learned that an integrated teaching and learning experience about motion is MESSY (i.e., it includes movement, engagement, social interactions, spontaneity, yikes, and yippees!). We engaged in a twofold goal process of integrating mathematics, science, and technology. First, we embedded an inquiry approach in our planning and facilitation of learnin...
1 CitationsSource
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