Conference Session

First Year Computing Topics

Collection

2017 ASEE Annual Conference & Exposition

Authors

Vanessa Svihla, University of New Mexico; Woong Lim, University of New Mexico; Elizabeth Ellen Esterly, University of New Mexico; Irene A Lee, MIT; Melanie E Moses, Department of Computer Science, University of New Mexico; Paige Prescott, University of New Mexico; Tryphenia B. Peele-Eady Ph.D., University of New Mexico

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

successfully increased women’s participation incomputer science through inclusive pedagogy in college classrooms [13, 14].Although there is increasing interest in learning computer science from both students and parents[15-17] barriers to accessing computer science courses in high schools still remain, includinglack of course offerings and inadequate technology [12, 15, 16, 18]. When students from groupsunderrepresented in STEM choose to enroll in an introductory computer science course, theyseldom find the topics engaging and relevant to their own lives [18-23]. The computing tasksthemselves might not be appropriately leveled, and if students face too much frustration at thebeginning of a course, this can negatively impact their self-efficacy in

Conference Session

CoED: Computer Science Topics

Collection

2017 ASEE Annual Conference & Exposition

Authors

Roxanne Moore, Georgia Institute of Technology; Michael Helms, Georgia Institute of Technology; Jason Freeman, Georgia Tech

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

participation with content-specific learning10. This belief maybe more prevalent among instructors with lower self-efficacy for teaching technical andcomputational content, as will be illustrated from a modeling perspective later in this paper.In this paper, we present causal loop diagrams that serve as explanatory models for the existenceof virtuous and vicious student engagement cycles11. These models serve as a guide forproposing professional development and implementation improvements for the future.Background: Modeling and Systems ThinkingSchools are complex systems with thousands of variables, feedback loops, social networks, andintelligent agents. They are difficult to predict and even more difficult to manipulate. It isdifficult to measure the

Conference Session

CoED: Embedded Systems and Robotics

Collection

2017 ASEE Annual Conference & Exposition

Authors

Ying Lin, Western Washington University; Todd D. Morton, Western Washington University

Tagged Topics

Diversity

Tagged Divisions

Computers in Education

understanding of the DSP topics covered in lectures, which might not be a good direct measure of student’s understanding of topics. However, it shows a relatively high level of students’ self-efficacy which can improve learning performance9, 10. Students also supported the use of this platform for future DSP offerings except for one student who pointed out that the selected K65 board might be too powerful for most senior design projects. As noted in Section III, we are currently investigating a similar but smaller size MCU board (i.e., the FRDM-K66F development board) as the alternative platform for the DSP laboratory coursework. This board could be a better option for some senior design projects compared