Conference Session

Computing and Information Technology Division Technical Session 3

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Caleb James O'Malley, University of Florida; Ashish Aggarwal, University of Florida

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology

researchershave studied various factors for their ability to influence the performance of a student in anintroductory programming course discussed below.1.1 Factors of SuccessA wide range of factors spanning from a student’s gender to their experience with video gameshave been studied in the context of student success in programming courses. Some of the mostcommonly analyzed factors include gender [3], [4], [5], [6], prior programming experience [3],[5] – [9], and previous math or science courses [3], [8]. Other factors include self efficacy [6],[8], comfort level [3], [6], [10], motivation [10], and attributions [6], [8].There is currently little evidence that gender plays a major role in student success. Quille et al.[4] conducted a multi-institutional

Conference Session

Computing and Information Technology Division Technical Session 3

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Margaret Ellis, Virginia Tech; Catherine T. Amelink, Virginia Tech; Stephen H. Edwards, Virginia Tech; Clifford A. Shaffer, Virginia Tech

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology

movesFigure 1: List of common problem-solving heuristics referenced in Problem Solving in ComputerScience courseStudents reported feeling intimidated, needing to teach themselves material required for courses,and that there was distance between students who had computing as a hobby and those who didnot 2 . Students identified tinkering and previous experience as an important part of feelingsuccessful in computer science. We are motivated to build students’ confidence and help thempersist in the field. We are inspired by previous work demonstrating that students’ sense of CSidentity, belonging, and self-efficacy is correlated with success 39,23,24 , and that tinkering andskill-building can improve these feelings 38 . We consider students’ comfort in a

Conference Session

Computing and Information Technology Division Technical Session 1

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Mia Minnes, University of California, San Diego; Sheena Ghanbari Serslev, University of California, San Diego ; Madison Edwards

Tagged Divisions

Computing and Information Technology

[school anonymized for publication] change as a result of your internship? How will yourexperiences this summer shape your approach to next quarter and beyond?” at the end of their internship.This mixed-methods approach helps us track students’ motivations, perspectives, and plans for action andsituates their internship as an integral part of their CSE undergraduate education.B. Background 1) The role of motivation in learning: Motivation is critical to learning and leads one to pursueand continue to pursue an objective [1, Part II]. Importantly, motivation is believed to be an emergentphenomenon, meaning it can develop over time and be updated based on new experiences. As described in[2], self-efficacy theory [3] and situational interest

Conference Session

Computing and Information Technology Division Technical Session 4

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Lina Battestilli, North Carolina State University; Sarah Korkes, North Carolina State University

Tagged Topics

Diversity

Tagged Divisions

Computing and Information Technology

variablespredefined. The second row shows Q5 Analyze-type questions for the treatment group and thecorresponding Q5 Create-type question for the control group.End-of-Lab SurveyAfter completing the auto-graded exercises, the students completed a survey, which was writtenusing validated questions from 24,25 . We asked the students self-efficacy questions and questionsabout their perception of the auto-graded exercises. Example Exercises Converted to Create-Type Q1: APPLY-type Q5: ANALYZE-type Table 3: Types of Auto-Graded ExercisesResultsLearning Efficiency (RQ1)Figure 2a shows differences in the number of attempts on each question between the two groupsthrough box-and-whisker plots with some outliers