Do you teach intro CS classes? Do you want your students to feel like they can succeed in your class?
We have been interviewing students to understand their perceptions of their programming abilities, and we've heard things like this in our interviews:
"I felt like I was behind and other people wouldn't take [...] as long."
"Having to use an outside resource [...] maybe I shouldn't have to use makes me feel like I could do better."
"If I'm really doing well, maybe I would just be able to figure it out as I'm coding and not have to stop."
"I [think] that programmers need to know every single little piece of syntax and every code and how to at least start doing everything."
"You think to yourself, 'oh, I should be understanding how to fix this. My friend would just do this right away.'"
"When I don't know where to begin or what I should write down first or import some data, I just feel like, 'oh, I'm really bad on programing.'"
Even though we in the computing community expect students to make mistakes, struggle with errors, have to look things up, ask for help, etc. when learning to program, students think they are doing poorly when they engage in these typical moments in the programming process! Why is this happening, and how can we help students set more realistic expectations for their programming and learning processes?
Virtual workshop summary
Session 1: August 7, 2024 @ 12-3 PM CDT (UTC-5) (in your time
zone)
In this first session, you will learn about recent research on student beliefs about their
programming
abilities and collaboratively brainstorm designs for classroom interventions to help
students
accurately
evaluate their ability.
Session 2: August 8, 2024 @ 12-3 PM CDT (UTC-5) (in your time
zone)
In this optional second session, you will have the opportunity to dive deeper and flesh out
the
designs
developed during the previous session.
Session 1: August 7, 2024 @ 12-3 PM CDT (UTC-5) (in your time zone)
In this first session, you will learn about recent research on student beliefs about their programming abilities and collaboratively brainstorm designs for classroom interventions to help students accurately evaluate their ability.
Session 2: August 8, 2024 @ 12-3 PM CDT (UTC-5) (in your time zone)
In this optional second session, you will have the opportunity to dive deeper and flesh out the designs developed during the previous session.
Workshop goals
Together with intro computing instructors who care about student motivation, you will...
- Learn about recent research on students’ expectations for their learning and programming
- Reflect on and share your existing practices that support students
- Brainstorm ideas for interventions you can try in your classes to help students develop more accurate expectations for their programming and learning processes
- Collaborate on designing, implementing, and evaluating your intervention ideas, if you are interested
Our goal for this workshop is for you to leave with more ideas for how to support students’ in developing a more accurate understanding of their own programming abilities.
If you are interested in testing these ideas in your classroom, we would love to chat to discuss potential collaborations!
Organizers
Dr. Eleanor "Nell" O'Rourke
Assistant Professor, Computer Science and
Learning
Sciences, Northwestern University
Eleanor "Nell" O'Rourke is an Assistant Professor in Computer
Science and the Learning Sciences at Northwestern University, where she co-directs
the interdisciplinary Delta Lab. Her research explores the design of novel
computational systems to support motivation and learning in STEM domains. Recent
projects include studying student beliefs about programming ability in introductory
computer science courses, designing game mechanics that encourage students to
practice effective problem-solving skills, and developing web inspection tools that
allow novice developers to learn directly from authentic professional websites. Her
interventions have been used by over 100,000 students online, adopted by companies,
and integrated into classrooms. Her work has been recognized through an NSF CAREER
Award, a Google Systems Research Award, and best paper awards and nominations at
SIGCSE, UIST, and CHI.
Website
Melissa Chen (she/her)
PhD Student, Computer Science, Northwestern
University
Melissa is a PhD student studying computer science in the Delta Lab at
Northwestern
University. Her work is on understanding how students evaluate their programming
abilities,
and
how to design social and technical interventions to help students develop more
accurate
expectations
for their programming abilities.
Website
Dr. Eleanor "Nell" O'Rourke
Assistant Professor, Computer Science and Learning Sciences, Northwestern University
Eleanor "Nell" O'Rourke is an Assistant Professor in Computer Science and the Learning Sciences at Northwestern University, where she co-directs the interdisciplinary Delta Lab. Her research explores the design of novel computational systems to support motivation and learning in STEM domains. Recent projects include studying student beliefs about programming ability in introductory computer science courses, designing game mechanics that encourage students to practice effective problem-solving skills, and developing web inspection tools that allow novice developers to learn directly from authentic professional websites. Her interventions have been used by over 100,000 students online, adopted by companies, and integrated into classrooms. Her work has been recognized through an NSF CAREER Award, a Google Systems Research Award, and best paper awards and nominations at SIGCSE, UIST, and CHI.
Website
Melissa Chen (she/her)
PhD Student, Computer Science, Northwestern University
Melissa is a PhD student studying computer science in the Delta Lab at Northwestern University. Her work is on understanding how students evaluate their programming abilities, and how to design social and technical interventions to help students develop more accurate expectations for their programming abilities.
Website