Conference Session

Using Computation and Modeling, Engineering Physics and Physics Division (EP2D) Technical Session 3

Collection

2023 ASEE Annual Conference & Exposition

Authors

Kristen Schumacher, University of Illinois, Urbana-Champaign; Sonali Joshi, University of Illinois, Urbana-Champaign; Jina Kang, University of Illinois, Urbana-Champaign; Eric Shaffer, University of Illinois, Urbana-Champaign; Jessica Raley, University of Illinois, Urbana-Champaign; Jose Nijaid Arredondo, University of Illinois, Urbana-Champaign; Brandon Mark Buncher, University of Illinois, Urbana-Champaign; Rajan Patkar, University of Illinois at Urbana-Champaign; Katherine Zine, University of Illinois, Urbana-Champaign; Daniel Alfredo Caballero, University of Illinois, Urbana-Champaign; Alexandria Tucker, University of Illinois, Urbana-Champaign; Mireille Tan, University of Illinois, Urbana-Champaign; Christopher Vistian, Physics Outreach at Illinois Through New Technologies

Tagged Divisions

Engineering Physics and Physics Division (EP2D)

given questionQ, we define Cohen’s d [43], including Hedges’ small sample size correction [44], as 2 3 N 2 µpost µpre 4 5, dQ = q 2 (1) pool N 2 N 1 2 2 2 (npre 1)s2pre + (npost 1)s2post pool

Conference Session

Using Computation and Modeling, Engineering Physics and Physics Division (EP2D) Technical Session 3

Collection

2023 ASEE Annual Conference & Exposition

Authors

Carlos Pineida, Universidad Andrés Bello, Chile ; Angeles Dominguez, Tecnologico de Monterrey, Mexico; Universidad Andres Bello, Chile

Tagged Divisions

Engineering Physics and Physics Division (EP2D)

ofinstructions before the implementation of the didactic methodology. Blue dots indicate students’ actual perception and orange dots indicate ideal perception of the type of instruction.Regarding the active subdimension, all six items (e, f, m, o, p, q) resulted with significantdifferences. In Figure 4, the shift of 3m to 4m indicates students’ perception of the need (in theirideal class) to preview concepts before class by reading, watching videos, etc., to solve problemsindividually during class (items 3o and 4o), or make individual presentations to the class (items(3e and 4e). These subdimensions indicate students’ willingness to active learning.Figure 5 shows the shift from actual class to ideal class corresponding to the interactive

Conference Session

Pedagogy in Physics Education, Engineering Physics and Physics Division (EP2D) Technical Session 1

Collection

2023 ASEE Annual Conference & Exposition

Authors

Johanna Antonia Perasso, Universidad Andres Bello, Chile; Angeles Dominguez, Tecnológico de Monterrey, Mexico; Universidad Andres Bello, Chile

Tagged Topics

Diversity

Tagged Divisions

Engineering Physics and Physics Division (EP2D)

to abandon the type of instructions that requires a passive role from them [23].This is discussed further in Figure 4 at the end of this section.Table 2Questions associated with type of instruction. Items with Description Factor Item significant difference Type of instruction Active e, f, m, o, p, q e, f, m, q Type of instruction

Conference Session

Engineering Physics and Physics Division (EP2D) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jason Morphew, Purdue University; Amirreza Mehrabi, Purdue Engineering Education; Ben Van Dusen, Iowa State University of Science and Technology; Jayson Nissen

Tagged Divisions

Engineering Physics and Physics Division (EP2D)

estimate student proficiency, CDMsuse latent classes to classify students by their mastery of underlying skills [40,42,43]. Skills cutacross content areas and multiple skills may be needed to correctly solve an item. CDMs areclassification models that aim to classify a student’s skill mastery for predetermined skillsidentified by content experts (See Table 1 for definitions). The skills require to correctly answer aquestion are coded dichotomously within matrix called the Q-matrix, which is used by DCMs toestimate mastery. While there are many CDMs, the simplest is the Deterministic Inputs, Noisy"And" gate (DINA) model. DINA is a crucial cognitive diagnostic tool to effectively estimate skillmastery, such as proficiency in applying vectors in

Conference Session

Engineering Physics and Physics Division (EP2D) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Junior Anthony Bennett, Purdue University; Jason Morphew, Purdue University; Michele W. McColgan, Siena College

Tagged Divisions

Engineering Physics and Physics Division (EP2D)

attention differently in examining physics diagrams? A study of change detection using the flicker technique,” Physical Review Physics Education Research, 11(2), 020104, 2015. https://doi.org/10.1103/PhysRevSTPER.11.020104 [36] J. W. Morphew, E. P. Kuo, Q. King-Shepard, P. Kwon, R. Lin, T. J. Nokes-Malach, and J. P. Mestre, “Seeing and doing are not believing: Investigating when and how conceptual knowledge impinges on observation and recall of physical motion,” Journal of Experimental Psychology: Applied, 27(2), 307-323, 2022. https://doi.org/10.1037/xap0000338[37] M. Perry, R. Breckinridge Church, and S. Goldin-Meadow, “Transitional knowledge in the acquisition of concepts,” Cogn. Dev., vol. 3, no. 4, pp. 359–400, Oct. 1988

Conference Session

Engineering Physics and Physics Division (EP2D) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Bala Maheswaran, Northeastern University; Rosalyn Bell Beckwith; Montserrat Velasco; Emily Minkler; Eleanor Altwarg, Northeastern University

Tagged Divisions

Engineering Physics and Physics Division (EP2D)

). [Accessed: 04-Dec-2022].[2] F. Orfei, “Introduction to vibration energy harvesting - technical articles,” All About Circuits, 19- Aug-2019. [Online]. Available: https://www.allaboutcircuits.com/technical-articles/introduction-to- vibration-energy-harv esting/. [Accessed: 04-Dec-2022].[3] “Industrial Monitoring Systems: Self-powered IOT systems from Revibe,” Revibe Energy, 22-Nov- 2022. [Online]. Available: https://revibeenergy.com/. [Accessed: 06-Dec-2022].[4] “Producing energy from vibrations,” AltEnergyMag, 16-Jul-2020. [Online]. Available: https://www.altenergymag.com/article/2020/07/producing-energy-from-vibrations/33439/. [Accessed: 04-Dec-2022].[5] Q. Zhao, Y. Liu, L. Wang, H. Yang, and D. Cao

Conference Session

Engineering Physics and Physics Division Technical Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

JAMES WANLISS, Anderson University

Tagged Divisions

Engineering Physics and Physics Division (EP2D)

. U., Bao Zhengrui, Song Xueying, and D. E. N. G. Wei. "Research on short-term load forecasting method of power grid based on deep learning." Modern electric power 35, no. 2 (2018): 43-48.[12] Shuvro, Rezoan A., Pankaz Das, Majeed M. Hayat, and Mitun Talukder. "Predicting cascading failures in power grids using machine learning algorithms." In 2019 North American Power Symposium (NAPS), pp. 1-6. IEEE, 2019.[13] Wanliss, J. A., and L. A. G. Antoine. "Geomagnetic micropulsations: Implications for high resolution aeromagnetic surveys." Exploration Geophysics 26, no. 4 (1995): 535-538. https://doi.org/10.1071/EG995535[14] Busby, Joshua W., Kyri Baker, Morgan D. Bazilian, Alex Q. Gilbert, Emily Grubert

Conference Session

Using Computation and Modeling, Engineering Physics and Physics Division (EP2D) Technical Session 3

Collection

2023 ASEE Annual Conference & Exposition

Authors

Ruben D. Lopez-Parra, University of New Mexico; Ravishankar Chatta Subramaniam; Jason Morphew, University of Illinois, Urbana-Champaign

Tagged Divisions

Engineering Physics and Physics Division (EP2D)

Conference Session

Engineering Physics and Physics Division Technical Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Emmabeth Parrish Vaughn, Austin Peay State University; Steven Warth, Austin Peay State University; Bobette Bouton, Austin Peay State University

Tagged Divisions

Engineering Physics and Physics Division (EP2D)