Alejandra J. Magana

Dr. Alejandra J. Magana

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Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 July 2020 in Computer Applications in Engineering Education
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JLJoseph A Lyon
Joseph A Lyon
AMAlejandra J. Magana
Alejandra J. Magana

1 December 2014 in CBE—Life Sciences Education
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Journal Article
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AMAlejandra J. Magana
Alejandra J. Magana
MTManaz Taleyarkhan
Manaz Taleyarkhan
DADaniela Rivera Alvarado
Daniela Rivera Alvarado
MKMichael Kane
Michael Kane
JSJohn Springer
John Springer
KCKari Clase
Kari Clase
Bioinformatics education can be broadly defined as the teaching and learning of the use of computer and information technology, along with mathematical and statistical analysis for gathering, storing, analyzing, interpreting, and integrating data to solve biological problems. The recent surge of genomics, proteomics, and structural biology in the potential advancement of research and development in complex biomedical systems has created a need for an educated workforce in bioinformatics. However, effectively integrating bioinformatics education through formal and informal educational settings has been a challenge due in part to its cross-disciplinary nature. In this article, we seek to provide an overview of the state of bioinformatics education. This article identifies: 1) current approaches of bioinformatics education at the undergraduate and graduate levels; 2) the most common concepts and skills being taught in bioinformatics education; 3) pedagogical approaches and methods of delivery for conveying bioinformatics concepts and skills; and 4) assessment results on the impact of these programs, approaches, and methods in students’ attitudes or learning. Based on these findings, it is our goal to describe the landscape of scholarly work in this area and, as a result, identify opportunities and challenges in bioinformatics education.

16 December 2016 in Computer Applications in Engineering Education
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AMAlejandra J. Magana
Alejandra J. Magana
GCGenisson Silva Coutinho
Genisson Silva Coutinho

15 February 2022 in Informatics
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JUJose Daniel Azofeifa Ugalde
Jose Daniel Azofeifa Ugalde
JNJulieta Noguez
Julieta Noguez
SRSergio Ruiz-Loza
Sergio Ruiz-Loza
JMJosé Martín Molina-Espinosa
José Martín Molina-Espinosa
AMAlejandra J. Magana
Alejandra J. Magana
Bedrich BenesBedrich Benes
Bedrich Benes
This document presents a systematic review of Multimodal Human–Computer Interaction. It shows how different types of interaction technologies (virtual reality (VR) and augmented reality, force and vibration feedback devices (haptics), and tracking) are used in different domains (concepts, medicine, physics, human factors/user experience design, transportation, cultural heritage, and industry). A systematic literature search was conducted identifying 406 articles initially. From these articles, we selected 112 research works that we consider most relevant for the content of this article. The articles were analyzed in-depth from the viewpoint of temporal patterns, frequency of usage in types of technology in different domains, and cluster analysis. The analysis allowed us to answer relevant questions in searching for the next steps in work related to multimodal HCI. We looked at the typical technology type, how the technology type and frequency have changed in time over each domain, and how papers are grouped across metrics given their similarities. This analysis determined that VR and haptics are the most widely used in all domains. While VR is the most used, haptic interaction is presented in an increasing number of applications, suggesting future work on applications that configure VR and haptic together.

1 February 2019 in Computers & Education
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CDChandan Dasgupta
Chandan Dasgupta
AMAlejandra J. Magana
Alejandra J. Magana
CVCamilo Vieira
Camilo Vieira

21 January 2022 in Journal of Engineering Education
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Journal Article
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AMAlejandra J. Magana
Alejandra J. Magana
TKTugba Karabiyik
Tugba Karabiyik
Paul ThomasPaul Thomas
Paul Thomas
Aparajita JaiswalAparajita Jaiswal
Aparajita Jaiswal
VPViranga Perera
Viranga Perera
JDJames Dworkin
James Dworkin
Background: We evaluated the effect of three teaching strategies to facilitate teamwork in a systems analysis and design course during the COVID‐19 pandemic: (1) offering a HyFlex version of the course, (2) facilitating scheduled online teamwork sessions for all students, and (3) providing conflict resolution training to help teams overcome collaboration challenges.Purpose/Hypothesis: To identify the impact of these instructional strategies and answer four research questions, we measured (1) performance, dynamics, and cooperation strategies of teams and (2) students' perceptions of their own and team members' performance along with changes in their perceptions of their conflict management skills.Design/Method: We used a simultaneous triangulation mixed‐methods design to obtain distinct but complementary qualitative and quantitative data. We compared data from two offerings of the course: Fall 2019 and Fall 2020 semesters. In the Fall 2019 semester, an in‐person active learning strategy was used, while in the Fall 2020 semester, the course followed a HyFlex delivery mode due to the COVID‐19 pandemic.Results: Findings suggest that the use of cooperative learning pedagogy along with HyFlex accommodations for safety and social distancing requirements for the Fall 2020 semester provided students with a comparable learning experience to a traditional in‐person mode.Conclusions: Learning strategies, pedagogical supports, and teamwork training can enhance social interactions, and consequently, students' social presence in online learning. Conflict resolution training could be a valuable tool for improving teamwork skills and communication among team members.