Robots, Recruitment, and Retention: Broadening Participation ...

Session F4H

Robots, Recruitment, and Retention: Broadening Participation Through CS0 Laura M. Grabowski, Pearl Brazier University of Texas-Pan American, [email protected], [email protected]

Abstract - Despite increasing demands for computing professionals in the global economy, interest in computing careers and their related university majors has declined steadily over the past decade, leading to challenges in recruiting undergraduate majors in computing programs. These problems are exacerbated when the university serves traditionally underrepresented groups and students who come from economically depressed communities. We present an innovative approach for a “CS0” course, designed to recruit and retain computer science and computer engineering majors at a Hispanic-serving university in the lower Rio Grande Valley of Texas. We use Lego® Mindstorms® NXT robots as the primary tool for learning algorithmic problem solving and fundamental programming concepts, in a supportive, social learning environment. We delivered the course during two semesters. One semester focused on increasing awareness about career possibilities in computing fields among female students, while the second semester’s class targeted retaining early computer science and computer engineering majors. Early assessments indicate that our approach is successful for our student population. Student interest in the course increased dramatically from the first semester to the next, and student engagement remained high during the semester. To date, the retention rate of the computer science and engineering majors who completed the course is 100%. Index Terms – CS0, Lego Robots, CS Recruitment, CS Retention

INTRODUCTION The decline in enrollments in the computing fields and more generally all STEM fields and the need for STEM professionals are well documented. Initiatives, both nationally and internationally, have been identified and put in place to address this problem. Efforts include targeting pre-college students beginning with middle schools and implementing college courses to attract more students. These efforts include revising content in required computer literacy courses or developing specialized courses as precursors to the traditional introduction to computer

science that relied heavily on programming in a high-level language. CS0 courses have been developed to provide for some introduction to algorithmic thinking skills and preprogramming skills targeted to students who are interested in majoring in computer science, but lack prior programming experience. UNIVERSITY DEMOGRAPHICS The University of Texas-Pan American [UTPA] is a regional comprehensive university located in the Lower Rio Grande Valley in Texas serving a population that is largely Hispanic and one of the poorest in the nation, with many first generation college students. The McAllen-EdinburgMission metropolitan area had the lowest per capita income (estimated at $7,001) in the United States in 1987. The student body at UTPA largely mirrors the Valley demographics. UTPA Demographics:  18,800 students, mostly commuter  85% undergrads, 3% post-baccalaureate, 12% graduate students  59% female, 41% male  86% Hispanic  Average age: 23 UG, 33 GR  Fulltime: 74% UG, 30% GR  First generation: 70%  Residency: o 93% Lower Rio Grande Valley o 77% directly from high school o 23% transfers: 80% of transfers from community colleges  19 Average ACT Score  1st year retention: 71.5%  2nd year retention: 56.6%  4-year graduation: 13.3%  5-year graduation: 28.3%  6-year graduation: 36.4%  7-year+ persistence: 11.8% GENERAL CONTEXT FOR CS0 There are numerous examples of the use of robots to attract and retain students in the computing field. Pierce [1] reports a CS0 course that can satisfy a practical reasoning requirement in the institution's general education program.

978-1-61284-469-5/11/$26.00 ©2011 IEEE October 12 - 15, 2011, Rapid City, SD 41st ASEE/IEEE Frontiers in Education Conference F4H-1

Session F4H This course included a required outreach assignment in which students demonstrate the robots and their programming to children in the larger community. Hood and Hood [2] report a CS0 course that uses Lego® Mindstorms® robots and a language developed to program the robots. Meyer [3] compares a CS0 course using Lego® Mindstorms® robots with one not using robots. He further discusses the use of robots through CS0 and more advanced courses. Beherns, et. al [4] describe the use of MATLAB to program the Lego® Mindstorms® robot. Summet et al [5], describe a CS1 course using a student purchased Scribber robot, programmed using a Python module. Carnegie Mellon [6] has funding to support recruiting and retention efforts for women as well as expanding the number of students entering the field. Many of our students begin their course of study at the university without adequate preparation in math or programming experience in high school. This fact prevents those students from entering the Computer Science I (CSI) course in their first semester. The CS0 course, entitled ―Introductory Computer Science Concepts,‖ was conceived as a means to provide some grounding in computer science concepts and fundamental programming skills for those less-prepared students, and to draw the students into the computer science community as soon as possible. Our vision for the course is to prepare students for programming and other computer science courses, as opposed to remediation for particular background deficiencies. The course is not a major requirement, but it fulfills the university’s core curriculum computer literacy requirement. Because of this fact, we included several key components from our computer literacy course in the CS0 course, such as application software skills and examination of social and ethical issues of computing. We taught the course in two semesters, with different target groups each semester. In the first semester (Semester 1), we aimed the course at female non-major students, with a goal of increasing awareness among female students about career possibilities in computing fields. For this group of students, we hoped that the course might generate enough interest to prompt some of the students to change majors to computer science or computer engineering. For the second semester (Semester 2), we focused on retaining early computer science and computer engineering majors through building conceptual understanding and student confidence before entry into CSI. CLASS ORGANIZATION AND COURSE OVERVIEW We focus the class organization on creating a supportive, low-stress learning environment, working to make the class meetings as enjoyable as possible for the students. Student engagement is a top priority in this course; even though there is ―serious‖ work going on, the process should be fun. Almost all the work for the course is hands-on, and accomplished during the class meetings. I. Class Organization

The environment of the class hinges on teamwork. Students are organized into small teams; for some projects, two teams might combine. Students work in teams, but are assessed individually. This approach fosters collaboration and peer mentoring while discouraging freeloading or cheating. The course staff is central to the students’ experiences in the course. The course instructor works closely with the students as they work through activities and assignments, providing feedback and suggestions. The relaxed atmosphere of the class helps put students at ease, so that they are more likely to ask the instructor questions. Through an award from the National Center for Women and Technology (NCWIT), we were able to bring in several student assistants to help with the course (two undergraduate assistants for Semester I, three undergraduate assistants and one graduate assistant for Semester 2) for the terms that we are reporting in this paper. The class assistants were critical to the support system and the atmosphere of the course in several ways, fulfilling many different support roles. Class assistants attended class meetings, helping students with assignments and the course instructor with evaluating completed assignments. The class assistants also held help hours outside of class meeting times. During help hours, students had access to the lab, computers, and robots, and could receive extra help or tutoring from the class assistants. The class assistants also provided out-of-class grading support for the course instructor, and performed regular maintenance on the class robots. In addition to these tangible support roles, the class assistants greatly enhanced the supportive environment of the class community, providing near-peer mentoring and strong role models for the students in the course. II. Course Overview The CS0 course existed prior to the semesters discussed in this paper. In previous offerings of the course, the content combined topics from another computer literacy course that we offer for the general student population (e.g., word processing, spreadsheets, web-based research) and an introduction to basic programming in C++. Following the NCWIT award, we redesigned the course to use Lego® Mindstorms® robots, to place more emphasis on problem solving and preparation for programming, and increase the attention to social and ethical issues. The course’s content addresses two broad areas, comprising computer literacy topics and fundamental computer science topics. Unlike the earlier course design, the two areas are largely integrated; there is not a discrete literacy ―unit,‖ per se, rather those activities and assignments are distributed across the semester. The computer literacy topics in the course include general computer background knowledge (e.g., hardware fundamentals, operating systems) and software skills (e.g., file management, word processing, web authoring). We give special attention to social and ethical issues related to computing. Students complete short written assignments in


Session F4H response to open-ended prompts, using sources found online to support their opinions. Example assignments include:  The Day the Computers Died: What would happen if all the computers in the world suddenly stopped working?  The Ethics of Artificial Intelligence: If we had the ability to create ―strong‖ AI, should we? How would those intelligent creations fit into the universe? What would our responsibilities be to these creations?  Future Computing Technology: Explore several future computing technologies (e.g., quantum computing, molecular switches, nano-computers, protonic memory), including when the technology may be ready for deployment. All the computer science concepts addressed in the course are viewed through the lens of the course’s core concept: algorithmic problem solving. Our objective is to prepare students for more demanding problems through solving simple and enjoyable problems. Through guided exercises and robot assignments, we help the students develop basic strategies for approaching problems. Some of the course assignments involve pure algorithm development and problem decomposition. For example, an early group activity involves developing an algorithm for completing an everyday activity (e.g., making a sandwich, sorting laundry). A particularly challenging assignment requires the students to reverse-engineer a robot program, by first observing the robot’s behavior, then puzzling out the algorithm behind the behavior, and finally programming their own robot to replicate the original robot’s behavior. All programming for the course uses the Lego® Mindstorms® robot. The programming assignments introduce students to basic control structures (sequence, decisions, looping) and modules. As the semester progresses, assignments grow more complex, culminating in a large final programming project. We emphasize algorithm design and development in all programs; the written algorithm is always submitted along with the program code, and is used as part of the evaluation of the robot’s behavior when programs are graded. The complexity of the programming projects is magnified by several changes to the robot’s body over the course of the semester. The first robot configuration is a simple two-wheeled design, with no sensors. Students can understand the mechanics of this simple robot intuitively, and are quickly successful in programming the robot. With this robot, students are concerned mostly with the two motors of the robot. Next, light/color sensors are added to the two-wheeled robot. Now students must contend with event-driven programs using the sensory input from the robot’s sensors. Near the end of the semester, the robot is reconfigured one more time into a humanoid form, with several different sensors. With this robot form, students need to design and program for three motors and various sensors (ultrasonic, light/color, touch), with more complicated interactions between the robot’s components.

COURSE DELIVERY There were some differences in the course between the two semesters of delivery that we discuss in this paper. These differences were influenced by three factors: 1) different target groups and class composition for the two semesters, 2) different class sizes, and 3) lessons learned from the first semester of course delivery. I. Target Groups and Class Composition The Semester 1’s target group was female non-majors. Registration for the course was initially controlled so that students needed special permission to enroll in the course. Only female students were permitted to enroll for a period of time. When the beginning of the semester was only a couple weeks away, the enrollment was opened to all students, and the permission requirement was removed. Due to this strategy, the class had a ratio of more than 4 female students to each male student. Because of the focus on women, we made a conscious choice to have an all-female course staff. The instructor was a female tenure-track faculty, and the student class assistants were female undergraduate students. One class assistant was a junior computer science major, and the other a junior non-major with a CS-I programming background. For the final project for Semester 1, the teams designed and programmed a dance for their robots. The students chose the music for their dance (approved by the instructor), designed and made a costume for the robot, and presented the completed dance on the final exam day. The final project demonstration was set up like a dance recital, with a program and an invited audience of computer science and engineering faculty. The target group for Semester 2 was current early computer science or computer engineering majors. There were no restrictions on registration for the course, and approximately half of the students enrolled were non-majors (13 out of 27 students). We retained the all-female course staff, but this fact was more coincidence than design. The same faculty member was the instructor for the course, and the original class assistants returned, joined by one additional undergraduate computer science major and one graduate computer science student. Semester 2’s final project was a maze-following task using certain sensory cues to determine the turns in the maze. For this project, we added an extra incentive of competition: the 5 fastest robots earned extra credit points for their programmers. To earn the extra credit, the robots had to be both quick and accurate: robots that hit obstacles or ran out of the maze were disqualified from the bonus points. With this problem, we exposed the students to the idea of optimization with multiple objectives. II. Impact of Class Size

The class enrollment for the Semester 1 was small, with 17 students. We assigned students to 3-4 person teams, with a total of 5 teams. We chose to keep teams all female or all male. Each team worked with one robot. The Semester 2 enrollment was noticeably higher than Semester 1, with 27 978-1-61284-469-5/11/$26.00 ©2011 IEEE October 12 - 15, 2011, Rapid City, SD 41st ASEE/IEEE Frontiers in Education Conference F4H-3

Session F4H students initially enrolled in the course. This time, we allowed students to self-organize in teams of two (with one 3-person team), making a total of 13 teams. The team members again shared a robot. The increased number of robots in Semester 2 greatly increased the overhead required for weekly robot maintenance. This fact spurred the doubling of the number of class assistants from 2 to 4 from Semester 1 to Semester 2. III. Lessons Learned Semester 1 was a pilot offering of the course. There were many unknowns going into the first semester, not the least being the use of the robots. The course staff, including the instructor, had limited prior experience with the Lego® Mindstorms® robots. This experience deficit was compounded when the robots for the course were received less than a month before the start of the new semester, making robot project planning difficult. Through most of the semester, the course staff was barely one assignment ahead of the students. We coped with this issue through regular staff meetings and frequent communication between classes. The class assistants took the lead in working out mechanical issues that arose with the robots themselves, freeing the instructor to focus on developing activities and assignments. We made the choice to have the student teams build their own robots, with the idea that building would be fun and engaging for the students, while reinforcing the notion of following an algorithm. This decision was an error in judgment. Several of the student teams experienced problems with erratic behavior (e.g., inconsistent turn angles, variation in distance travelled, different leg movement in the humanoid robot) from their robots, persisting over several reconfigurations of the robot body. Finally, we began to check the robots for building errors, and found that the teams experiencing problems had made mistakes in building the robots. The class assistants rebuilt all the affected robots, spending 3-4 hours on each robot. We remedied this problem in Semester 2 by having the class assistants do all the critical steps of the robot assembly. Students were given partially assembled components to assemble, and the class assistants checked each robot for errors before programming began. In Semester 1, teams worked together on all the robot assignments, completing one solution for the whole team. Guidelines for the assignments stipulated that all team members must work on all aspects of the assignment. For some teams, this arrangement worked well: each team member was fully invested in the process, and contributed equally to each part of the assignment. For other teams, however, the process was not as smooth. Some groups had one dominant team member who took control of the robot; some students were resistant to the procedure of developing the algorithm before programming. As a result, some teams worked harmoniously while others were contentious. In Semester 2, we changed the structure of assignments such that students worked in teams but completed individual

assignments. Teammates were permitted to help each other, but not give each other solutions. Although difficult to enforce, this policy led to a more equitable feeling and fewer conflicts between team members. OUTCOMES Early informal assessments suggest that our approach is successful for the student population at our university. It is too soon to report quantitative downstream data for the students who completed this course. Of a class of 24 in Semester 2, 50% of the students were computer science or computer engineering majors and all are continuing in those same major programs. An additional two students changed to computer science/engineering. 58% of the major students have enrolled in subsequent computer science courses. Another indicator of success is the dramatic increase in course enrollment from Semester 1 to Semester 2, an increase of 59% (from 17 to 27 students at the start of the term). This increase is a sign of student interest in the course. Students remained very active and engaged throughout the semester. Attrition rates (i.e., student drops) in this course were very low: in Semester 1, no students dropped the course after the initial first-week schedule adjustment period, and only 2 students dropped in Semester 2 (both for personal, non-academic reasons). Absenteeism was similarly low, with nearly perfect student attendance for all class meetings (on average, fewer than 2 students absent on any given class day). Student drops and class absences tend to be high at our university, so the low incidence of both of these phenomena suggests that the course holds onto student interest throughout the term. Unlike other computer literacy courses that we offer, students in the CS0 course completed nearly all required work for the course, and submitted those assignments on time, another indicator of student engagement in the activities of the course. Informal feedback from students was very positive. Most students indicated that they enjoyed the relaxed, supportive atmosphere of the class, and found the instructor and the class assistants approachable and helpful. When students had negative feedback, it was without exception related to the written assignments for the course. They enjoyed the robot work and the team assignments, but not the social and ethical issues assignments. We do not find this information in the least surprising, since many of our students struggle initially with writing assignments of any kind. CONCLUSION

Although the methods we describe in this paper are not new, we introduced those methods to a unique student population with unique needs and challenges. We are encouraged by the performance and retention of the students in this course, and look forward to further observing the downstream impacts of this course. As part of a larger curriculum initiative, we are applying the ideas and lessons learned from this course in a 978-1-61284-469-5/11/$26.00 ©2011 IEEE October 12 - 15, 2011, Rapid City, SD 41st ASEE/IEEE Frontiers in Education Conference F4H-4

Session F4H new, required CS0 course. The new course, to be taken by entering computer science majors and entitled ―Introduction to Computer Science,‖ draws heavily on the approaches, methods, and content of the course we present in this paper. Our hope is that all of our computer science major students can enjoy the benefits of this type of hands-on course, delivered in a supportive and cooperative environment. ACKNOWLEDGMENT Partially funded by National Center for Women & Information Technology (NCWIT) Seed Fund Award, ―Dancing Robots Introduction to Computer Science‖ 2009. REFERENCES [1]

Pearce , Janice L. ―Requiring outreach from a CS0-level robotics course‖, Journal of Computing Sciences in Colleges, Vol. 26 Issue 5, May 2011, 205-212

[2]

Hood, Cynthia S.& Dennis J. Hood, , ―Teaching programming and language concepts using LEGOs‖, ITiCSE, 2005, 19-23.

[3]

Meyer, Mark, ―Robots: an educational revelation in CS at a Jesuit College‖, cs.canisius.edu/~robotics/PowerPoints/csta.ppt. Accessed April 2011.

[4]

Behrens, A. Atorf, L. Schwann, R. Neumann, B. Schnitzler, R. Balle, J. Herold, T. Telle, A. Noll, T.G. Hameyer, K. Aach, T. ―MATLAB Meets LEGO Mindstorms—A Freshman Introduction Course Into Practical Engineering‖, IEEE Transactions on Education, Vol. 53, No. 2, May 2010, pp. 306 – 317.

[5]

Summet, J., Kumar ,D. et. al, ―Personalizing CS1 with Robots‖, SIGCSE’09, ACM 2009.

[6]

Carnegie Mellon's women@SCS Outreach roadshow, http://women.cs.cmu.edu/What/Outreach/Roadshow/ retrieved November 23, 2010.

AUTHOR INFORMATION Laura M. Grabowski, Assistant Professor, University of Texas-Pan American, [email protected] Pearl Brazier, Associate Professor, University of TexasPan American, [email protected]
