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Wednesday, May 25, 2011


Here is a quote on Change from a book by James Baldwin, "Nobody Knows Me." It made me think of what we are trying to do with SUSTAIN-SLO.

"Any real change implies the break up of the world as one has always known it, the loss of all that gave one identity, the end of safety. And at such a moment - unable to see and not daring to imagine what the future will now bring forth - one clings to what one knew or thought one knew, to what one possessed or dreamed that one possessed. Yet it is only when man is able, without bitterness or self-pity, to surrender a dream he has long cherished, or a privilege he has long possessed, that he is set free - that he has set himself free for higher dreams, for greater privileges."

Tuesday, May 24, 2011

How it might work...

I posted my version of "the day in the life" of a SUSTAIN faculty and how I'd prepare to be involved in this.  My posting is at the public site.

I have to say that this process of working with one another is really fun for me...getting to see what others are thinking, how they are thinking...this is really what I thought university life would be like when I came to Cal Poly 20 years ago.  I'm glad I'm finally learning together.

Monday, May 23, 2011

A need for structure

As I think probably became clear last week, I'm a details and process person. I spent my time last week trying to logistically account for the six different courses we're trying to offer next winter. How will we be able to "prove" to the administration and other departments that students are meeting the guidelines for a 4- or 5-unit course? I *think* I figured out a way, and I shared it last week. To me, nothing can move forward until we determine this issue, whereas other people thought I was crazy. But accountability matters in issues like these, and if we want to convince faculty and students to participate, I think we have to show them how it might work. We're talking about 100 students here--the positive impact could be huge, but so could the negative.

I am still struggling to figure out some logistical details, and realize that I still don't have a good sense of how "Sustain" time will work. For instance, if we're saying that 2-5 M-F is Sustain time, what does that mean in terms of classroom space? If Physics 121 and PSC 101 can meet at the same time with the same instructor, where will they meet? Will there be a room big enough for 70 students? And will the space be conducive to active learning (i.e. not lecture, but other types of classroom activities)? Space constraints are a huge issue in my department, as we do a lot of groupwork and are often "stuck" in classrooms that have immovable desks. What about labs for these 70 students? Will there be lab space to accommodate them all during the Sustain times? And, how will students know where to go each day? That is, if HIST 216, PHYS 121, COMS 102, and PSC 101 all meet from 2-5 M-F, how will students know which classroom/lab to go to on which day? And, if some students are taking COMS 102, but others are taking ENGL 134, what will the ENGL 134 students be doing during the Sustain time that focuses on COMS 102? Presumably they will have already had that course, so what would they do with those hours in the day?

These questions seem picky and small to some--like details that can be ironed out later. But in my experience with curriculum planning, it's details like this that can make or break a project. I don't need to know what will happen in each of those courses; I agree that what unfolds will be un-plannable to an extent. But I need to understand the structure for students and for faculty--where they will go when. Or I at least need to see a possible plan for structure, rather like my possible plan for how these courses could be scheduled during those hours. I think a good many faculty are in my position, and I think the project will be more successful if we can demonstrate that we've thought these things through as far as possible. There will always be hiccups along the way, but planning is key.

Statistics Narrative

In the time between the 12 May and 17 May meetings, Linda asked the group to contemplate a narrative about what the experience would be like for our individual fields. I attempted to draft a narrative, but it only yielded a silly tale which leaped around and between class functionality to my/our own preparation. Linda shared her narrative at the 17 May meeting. It appeals to me because much of the process is very similar to my own preparation process. I am eager to see a graphic of her narrative for future visual reference and recollection. From the perspective of the statistics partner, the only preparatory consideration I must mention are the projects. Before the experience begins, the statistics partner must be familiar with the projects, their individual goals, the individual data, and similarities/differences in and between the various data. Ideally, much of the data will have already been collected or will be collected in the first few weeks of the term.
The statistics learning objectives will be best experienced in the second term, an ideal term to support the collaborative effort. The projects will form the basis for student engagement. Having statistics in the second term will allow time for the projects to mature to include data collections. It is possible that not every project will have traditional data or practical data analysis needs to be successful. However, this may result in students collaborating on multiple projects (perhaps good), projects which are too complex, and/or not ideally aligned with the statistics learning objectives.
When the term begins, each student will be given a syllabus for their respective course, which includes the learning objectives and a tentative outline of when learning objectives and/or topics need to be attained. I will show all of the students all of the learning objectives from each course, so that they can see the overlap in learning objectives and topics. I will identify learning objectives which are similar and capable of attainment through projects collectively, learning objectives which cannot be taught through projects, and learning objectives which are specific to their course. Learning objectives in the last two categories are likely to be attained through supplemental online tools, suggested readings, short lectures, and small group discussions as needed.
There are no impossibilities about the structure of student contact time. This could range from traditional/structured lectures, to days/times devoted to small group interactions specific to individual projects/groups. I envision a hybrid approach where all students are present. Students will arrive having done some independent learning, which may not entirely be connected to their project. The independent learning tools will have self-assessment exercises and, perhaps, a formal graded quiz. Students will have to think through and develop questions related to their project. The students will bring their data and questions to the 'class room' which ought to be a computer lab (eg the statistics studio 02-206).
We begin with a real question: 'student X wants to use his/her data to answer question X1.' Connections across the projects will further develop, if not already, when student Y recognizes similarities and offers: 'student X's question X1 is just like my question Y1.' Then, we will talk about about what statistics are appropriate, what are inappropriate, a little theory, some assumptions, software use, and examples in the context of the student projects. The contact time should utilize the statistics partner as a coach or guide, devoting ample time to students working in teams to analyze project data.
I have written this narrative with lots of possibilities, but there are some conceptual and practical impossibilities to consider.
1. Projects
The projects must be well organized, and have a minimal set of diverse data types (qualitative and quantitative variables). Students with projects that do not have this will need to 'partner' with other groups. As a consequence, students may feel like they are working on multiple projects - which isn't necessarily a negative. Alternatively, related data could be identified and utilized.
In general, students will have to accept that concepts learned though projects will occur gradually, somewhat sequentially, and over time. Students will not obtain an ideal, global data analysis rapidly or at the beginning of the experience.
2. Grading
To have support from the senior statistics faculty, traditional grading will have to be used to determine official university grades. This may be some combination of online quizzes, project related homework, a project report which demonstrates mastery of the statistics learning objectives (likely part of a larger report), at least one midterm, and a final.