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1. An analysis of students’ mathematical models for music

   Corum, K.; Kara, M.; Talbot, E.; Ilina, T. (January 2020, Proceedings of the Forty-Second Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education.)

   This paper describes a modeling task designed to improve students’ understanding of music and related unit structures (e.g., whole note, half note). Fourteen upper elementary students were asked to build models of melodies using Cuisenaire rods and make arguments about how their models represented what they heard. Our analysis of students’ models suggested four categories of models. Students exhibited one- or two-dimensional reasoning with either (or both) height and length correspondence that varied in terms of duration and/or pitch features. 

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2. Disability and Invisibility in STEM Education

   https://doi.org/10.33423/jhetp.v20i14.3854  

   Schneiderwind, Joseph; Johnson, Janelle M. (December 2020, Journal of Higher Education Theory and Practice)

   null (Ed.)

   Across STEM fields, the education system continues to “weed out” students from non-dominant communities. Most studies on the damaging effects of underrepresentation focus on minorities or women in STEM fields. We examine some of the research about students with disabilities and note the limited literature on this subject. University enrollment by students with disabilities has increased in the last two decades while the amount of corresponding research published has decreased. This issue should not be siloed to disability studies- it is one that must be recognized by all educators. We conclude with some practical suggestions on how to move forward. 

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3. Mental models, cognitive maps, and the challenge of quantitative analysis of their network representations

   https://doi.org/10.1002/sdr.1729  

   Haque, Sumaiya; Mahmoudi, Hesam; Ghaffarzadegan, Navid; Triantis, Konstantinos (February 2023, System Dynamics Review)

   Abstract Cognitive maps, or mental maps, are externalized portrayals of mental models—people's mental representations of reality and their presumptions about how the world works. They are often used as the intermediary step toward uncovering individuals' presumptions of the outside world. Yet, the next step is often vague: once one's understanding of the real world is mapped, how can we systematically evaluate the maps and compare and contrast them? In this note, we review several common approaches to analyzing cognitive maps, some rooted in network theories, and apply them to a dataset of 30 graduate students who analyzed a complex socioenvironmental problem. Our analysis shows that these methods provide inconsistent results and often fall short of capturing variations in mental models. The analysis points to a lack of effective methods for examining such maps and helps articulate a major research problem for systems‐thinking scholars. © 2023 System Dynamics Society. 

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4. Effect of Three Classroom Research Experiences on Science Attitudes

   https://doi.org/10.26077/f5d3-9317  

   Lucas, Lauren K.; Hunter, Frances K.; Gompert, Zachariah (October 2020, The journal on empowering teaching excellence)

   null (Ed.)

   Here we evaluate undergraduate student attitudes about science after each of three authentic research experiences in a semester of an introductory biology laboratory course at Utah State University. The three course-based research experiences (CUREs) vary in length and student freedom, and they cover different areas of biology. Students responded to the science attitude items of the CURE Survey. When compared to national data, our students faired similarly, and all students struggled with certain epistemic assumptions about science knowledge. As also seen in the national database, change in science attitude was slight and nonlinear. Student self confidence in what a career scientist is and in scientific process skills was the best predictor of scientific maturity, not the three CUREs or other aspects of students’ background. We discuss the slight positive and negative change in attitude we did influence, and we note that most students would choose to have another research experience. 

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5. Native American engineering faculty: Insights into entry and persistence

   Authors: Jacobs, S. C.; Johnson, S. B.; Lee, K.; Colston, N.; Mason-Chagil, G.; Turner, S. L.; Presenters: Turner, S. L.; Mason-Chagil, G. (April 2019, Keeping Our Faculty VIII: Recruiting, Retaining, Advancing American Indian Faculty and Faculty of Color)

   Science, technology, engineering, and mathematics (STEM) education initiatives in higher education increasingly call for career mentorship opportunities for underrepresented minorities (URM). Researchers (Johnson & Sheppard, 2004; Nelson & Brammer, 2010) note the importance of having faculty to mentor and act as role models for students, often assuming that mentors play a stronger role if they are also from the same cultural background. Native American (NA) faculty members are underrepresented in most fields in colleges and universities, and exceedingly so in engineering. Only 0.2% (N=68) of engineering faculty nationwide identify as Native American (Yoder, 2014). Likewise, NA students are underrepresented in undergraduate (0.6%; N=1853) and graduate (0.1%; N=173) engineering programs. The low percentage in graduate school is of even greater concern as they represent the primary potential pool of new faculty members. Advising and mentorship from those who identify as NA are often considered important components recruiting and retention in STEM fields. For example, Smith and colleagues (2014) found that factors such as communal goal orientation influenced NA engineering students’ motivation and academic performance. However, very few studies account for differences in NA identity or provide a nuanced account of successful NA STEM professional experiences (Page-Reeves et al., 2018). This research paper presents findings from an exploratory study aimed at pinpointing the factors that influence NA entry and persistence in engineering faculty positions. 

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