Alejandra J Magana
Biographic Data
| ID | 6770033 |
|---|---|
| NAME | Alejandra J Magana |
| GIVEN NAMES | Alejandra J |
| FAMILY NAME | Magana |
| SIGNATURE | MAGANA A J |
| AFFILIATIONS | Purdue University West Lafayette |
| ORCID | 0000-0001-6117-7502 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Model-based reasoning in STEM education: A systematic literature review
Assessing Disciplinary Teachers'Pedagogical and Content Knowledge in Computational Thinking
Undergraduate students’ models of single- and multi-electron atoms
Quantum physics forms the basis for exciting new technologies, including quantum computers, quantum encryption, and quantum entanglement. The advancement of science and technology highlights the importance of mastering quantum physics and its applications, not only at the college level but also as early as high school. In this multiple case study, we investigated first- and second-year undergraduate college students’ models of single and multi-el…
Characterizing Team Cognition Within Software Engineering Teams in an Undergraduate Course
Contribution: The study characterizes aspects of cognitive and metacognitive dimensions of team cognition of software development teams in educational settings. Background: The software development industry requires software engineers and developers to work in teams; for this, there is substantial research on teamwork in the context of the organization. However, little is known about it in the context of educational settings, where there is scant…
Characterizing the psychosocial effects of participating in a year-long residential research-oriented learning community
Characterizing the Identity Formation and Sense of Belonging of the Students Enrolled in a Data Science Learning Community
Student attrition is a challenge experienced by higher education institutions. One of the key reasons for student attrition is the inability of students to develop an identity and a sense of belonging. This study aims to understand the role of a data science learning community in helping students to develop identity and a sense of belonging. The study used a mixed-methods approach to collect and analyze the data. The study used a pre–post survey …
Emotional and cognitive effects of learning with computer simulations and computer videogames
Characterizing Team Orientations and Academic Performance in Cooperative Project-Based Learning Environments
Information technology professionals are required to possess both technical and professional skills while functioning in teams. Higher education institutions are promoting teamwork by engaging students in cooperative and project-based learning environments. We characterized teams based on their collective orientations and evaluated their team performance in a cooperative project-based learning environment situated in a sophomore-level systems ana…
Classroom orchestration of computer simulations for science and engineering learning: A multiple-case study approach
This multiple case study focused on the implementation of a computer-aided design (CAD) simulation to help students engage in engineering design to learn science concepts. Our findings describe three case studies that adopted the same learning design and adapted it to three different populations, settings, and classroom contexts: at the middle-school, high-school, and pre-service teaching levels. Although the classroom orchestration of the partic…
Investigating Students’ Habits of Mind in a Course on Digital Signal Processing
Contribution: Knowledge of students' Habits of Mind in a signal processing course, and a method for education research. The method identifies factors that may influence students' performance, but are not evident when analyzing agglomerated data; it is an alternative to the traditional case study method as it derives the cases after applying a clustering approach. Background: Habits of Mind refer to mathematical, logical, and attitudinal modes of …
Exploring Undergraduate Students’ Computational Modeling Abilities and Conceptual Understanding of Electric Circuits
Contribution: This paper adds to existing literature on teaching basic concepts of electricity using computer-based instruction; findings suggest that students can develop an accurate understanding of electric circuits when they generate multiple and complementary representations that build toward computational models. Background: Several studies have explored the efficacy of computer-based, multi-representational teaching of electric circuits fo…
Characterizing Engineering Learners’ Preferences for Active and Passive Learning Methods
This paper studies electrical engineering learners' preferences for learning methods with various degrees of activity. Less active learning methods such as homework and peer reviews are investigated, as well as a newly introduced very active (constructive) learning method called “slectures,” and some others. The results suggest that graduate students' perception of the usefulness of the activity increases with its level of activity. For undergrad…
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Exploring Undergraduate Students’ Computational Modeling Abilities and Conceptual Understanding of Electric Circuits
Contribution: This paper adds to existing literature on teaching basic concepts of electricity using computer-based instruction; findings suggest that students can develop an accurate understanding of electric circuits when they generate multiple and complementary representations that build toward computational models. Background: Several studies have explored the efficacy of computer-based, multi-representational teaching of electric circuits fo…
Characterizing Engineering Learners’ Preferences for Active and Passive Learning Methods
This paper studies electrical engineering learners' preferences for learning methods with various degrees of activity. Less active learning methods such as homework and peer reviews are investigated, as well as a newly introduced very active (constructive) learning method called “slectures,” and some others. The results suggest that graduate students' perception of the usefulness of the activity increases with its level of activity. For undergrad…
Investigating Students’ Habits of Mind in a Course on Digital Signal Processing
Contribution: Knowledge of students' Habits of Mind in a signal processing course, and a method for education research. The method identifies factors that may influence students' performance, but are not evident when analyzing agglomerated data; it is an alternative to the traditional case study method as it derives the cases after applying a clustering approach. Background: Habits of Mind refer to mathematical, logical, and attitudinal modes of …
Characterizing Team Orientations and Academic Performance in Cooperative Project-Based Learning Environments
Information technology professionals are required to possess both technical and professional skills while functioning in teams. Higher education institutions are promoting teamwork by engaging students in cooperative and project-based learning environments. We characterized teams based on their collective orientations and evaluated their team performance in a cooperative project-based learning environment situated in a sophomore-level systems ana…
Classroom orchestration of computer simulations for science and engineering learning: A multiple-case study approach
This multiple case study focused on the implementation of a computer-aided design (CAD) simulation to help students engage in engineering design to learn science concepts. Our findings describe three case studies that adopted the same learning design and adapted it to three different populations, settings, and classroom contexts: at the middle-school, high-school, and pre-service teaching levels. Although the classroom orchestration of the partic…
Characterizing the Identity Formation and Sense of Belonging of the Students Enrolled in a Data Science Learning Community
Student attrition is a challenge experienced by higher education institutions. One of the key reasons for student attrition is the inability of students to develop an identity and a sense of belonging. This study aims to understand the role of a data science learning community in helping students to develop identity and a sense of belonging. The study used a mixed-methods approach to collect and analyze the data. The study used a pre–post survey …
Emotional and cognitive effects of learning with computer simulations and computer videogames
Characterizing the psychosocial effects of participating in a year-long residential research-oriented learning community
Undergraduate students’ models of single- and multi-electron atoms
Quantum physics forms the basis for exciting new technologies, including quantum computers, quantum encryption, and quantum entanglement. The advancement of science and technology highlights the importance of mastering quantum physics and its applications, not only at the college level but also as early as high school. In this multiple case study, we investigated first- and second-year undergraduate college students’ models of single and multi-el…
Characterizing Team Cognition Within Software Engineering Teams in an Undergraduate Course
Contribution: The study characterizes aspects of cognitive and metacognitive dimensions of team cognition of software development teams in educational settings. Background: The software development industry requires software engineers and developers to work in teams; for this, there is substantial research on teamwork in the context of the organization. However, little is known about it in the context of educational settings, where there is scant…
Assessing Disciplinary Teachers'Pedagogical and Content Knowledge in Computational Thinking
Model-based reasoning in STEM education: A systematic literature review
Psychology (11 works) · Mathematics education (9 works) · Computer Science (8 works) · Innovative Teaching and Learning Methods (5 works) · Artificial Intelligence (4 works) · Artificial Intelligence (3 works) · Cooperative learning (3 works) · Educational technology (3 works) · Science Education and Pedagogy (3 works) · Social Psychology (3 works)