1. Briefly list the most significant issues in science education facing you and your institution
Notes from Henry M. Walker
I expect that many significant issues facing science education may be disciplinary in nature, and it might be useful to consider some matters related to specific disciplines as well as those that are more general.
Here are some thoughts regarding issues that may transcend disciplines.
- Breadth/Depth at the Introductory Level: There seems to be considerable interest in having an introductory course provide a broad survey of the discipline, so that students can get an early view of what it is like to work in that discipline. At the same time, many disciplines expect later courses to build upon the foundations laid in those first courses, and this raises questions as to how breadth can co-exist with depth. For example, in the 1990s, a number of computer scientists promoted a "breadth-first" curriculum for introductory computer science. Various proposed introductory courses touched on many interesting topics and gave a lovely overview of the field. However, these proposed courses never covered any topic in much detail, and all later courses had to start from the beginning again. In effect, the introductory courses added an extra course to a CS major, and this "breadth-first" approach was not widely adopted in the 1990s. I have heard similar proposals for a different type of mathematics course (e.g., not starting with calculus) or for physics, but these ideas do not seem to have gained much general support.
- Sharing Course Materials: Many introductory science courses have moved to a lab-based model, in which students spend much time exploring and discovering concepts following an active pedagogy. To support this approach, faculty typically spend a substantial amount of time developing lab materials, exercises, etc. However, in my experience, faculty often start development of these lab-based courses from scratch; at least in computer science, we are not very good at drawing upon labs developed from faculty at other institutions. This raises the question of whether ACM schools might collaborate in some way to share course materials.
- Attracting Students: Particularly in computer science, much attention is being paid nationally to the dramatic drop in enrollments in recent years. At many schools, the number of CS majors may be down 40%-50% since 2001. This has led to numerous conversations about how to attract students – particularly women and those from underrepresented groups, so they will try the discipline relatively early. Introductory courses may be wonderful, but we can only capture the attention of students if they try our courses fairly early. Of course, most every department will have a similar perspective, but science departments tend to have longer prerequisite chains than non-science departments, and getting started early may be particularly important in the sciences.
- Interdisciplinary work: Much attention has been paid recently regarding interdisciplinary work. Schools are strongly encouraging faculty to collaborate on new courses that bridge disciplines, and this can yield to exciting courses and research. At the same time, many interdisciplinary efforts require a strong grounding in specific subject areas. This raises the issue of how to maintain a strong core curriculum within a discipline while also reaching across disciplinary lines.
Related to interdisciplinary work, I would raise a few questions of positioning: New introductory-level courses, to attact pre-disciplinary students? New advanced courses, fostering collaboration between students already grounded in disciplines? Can existing core courses incorporate interdisciplinary components or modules without losing their disciplinary perspective?
I would also add the issue of the title of the workshop "pedagogies of engagement": How can we help students become self-directed, self-monitoring learners, especially as preparation for learning on their own after leaving college? There are no textbooks or classes for much of what students will need to learn later, whether in research or industry.
Henry has a great list started. One of my biggest struggles is that there are always tends to be a few talented students who don't appreciate the open ended nature of inquiry based learning. It is difficult to convince some students that there are many possible solutions and no "best" model.
The NSF has recently supported a statistics web resource, Causeweb, filled with example labs, datasets, project ideas, current research in stat education, etc...It is a nice resource for finding course examples at all levels of depth, giving interdisciplinary examples and making labs/classes fun for students.
- Students don't have solid foundational skills in algebra and quantitative reasoning.
- Students are reluctant to write about technical material and do not see the value in communicating technical ideas or explanations.
2. Which of these problems do you think would lend themselves to collaborative efforts at solution?
Notes from Henry M. Walker
Each area from question 1 (introductory breadth/breadth, sharing materials, attracting students, and interdisciplinary work) would seem to transcend schools within ACM. Some issues might have a disciplinary component, so discussions might need to group ACM faculty by disciplinary.
Beyond these issues, the general subject of lab-based courses arises frequently, and it might be worth discussing various models for lab-based courses that encourage collaborative learning.
It seems that faculty of different disciplines could learn a lot from each other about methods for structuring the classroom and course work to promote engaged learning. It's sometimes not clear to me what methods are "typical" even within my own discipline.
I often try to include collaborative interdisciplinary examples in my class, however it is difficult to find faculty motivated to take the extra time and energy to truly create authentic interdisciplinary examples. As a statistician, I am always a little surprised that more faculty are not interested in incorporating quantitative analysis into their courses.
I would like to know how other schools address (a)—is remedial work desirable at good colleges? If so, can it be done in a way that does not make students feel like they were terribly let down by their high schools?
I would like to know what types of writing/communication of technical ideas other schools use in science education. How do we get our students excited about writing?
3. Are there any other issues that you seek collaboration among your ACM colleagues?
Notes from Henry M. Walker
I would be interested in talking to computer scientists from other ACM colleges about specific curricular issues related to our computer science programs.