Wednesday, April 20, 2011

Read, write, learn (Part 2)

Continuing with the second part of this two part blog, my goal is answer this question:  How does MLCS embody the characteristics of a quality higher education set forth by Academically Adrift?

1.  We’re asking them to read and write often.
Being able to process information that comes in print form is a valuable skill.  Throughout the course, we are using articles from the news to motivate content and illustrate concepts.  One comment we have received numerous times when faculty see our choice of articles is “what if they can’t read them?”  Keep in mind we’re not choosing scholarly journal articles but instead articles that have the reading level of a mainstream blog or newspaper.  In other words, something entirely expected for an adult.  Yes, there will be students who struggle.  But instead of removing the demands and rigor that reading brings, we’ve chosen to address that concern and teach reading strategies.  Through research and talking with reading instructors, we’re gathering a set of techniques that we’ll embed into the course.  Students will have to try each technique once and then determine which works best for them.  Once they do, they’ll be asked to use it from that point forward. The key point is that students learn how to read better by reading.  Our goal is to help them do that in an approachable way.

Writing comes in the form of brief explanations on written assessments, forming more detailed explanations on open ended assessments, and journals.  Beyond the expected "show your work” instruction that is seen often on math tests, we want them to explain their reasoning and thought process.  It’s not about mimicking our method but instead defending and supporting whatever approach they use.

For both reading and writing, we’re developing ways to keep students accountable.  In other words, they have to read something or write something and then do a follow-up quiz or assignment to prove understanding.  Students don’t do optional so we’re forcing accountability.  They’ll thank us someday.
2.       MLCS is a rigorous course.

Rightfully, many faculty are skeptical of the MLCS course at the concept stage.  I’ve been asked directly, “aren’t you just dumbing down content and rushing them through developmental math?”  Unequivocally, no.  The goal of the course is to differentiate content based on student goals and needs.  The reality is that if you’re going to get an Associate of Arts, which requires statistics or general education math, you don’t need to be able to add rational expressions.  We can debate the merits of topics and never agree.  But we currently spend millions of dollars working to get students through courses that do little to grow their critical thinking skills or have any discernable payoff.  If they’re headed toward STEM paths, yes, the traditional content makes more sense.  But right now, it’s way too much of symbolic manipulation for the sake of it for many students.  Those same students need better reasoning skills that directly apply to mathematics and they’re not getting them.  So the main argument for the course is not to scrap algebra.  But instead teach algebra that makes sense and add some other topics that would benefit students as well.
When you bring in other topics like geometry, statistics, open-ended problems, and analysis of structures in addition to many traditional algebra topics, you get a very rigorous course.  Content can be very challenging and demanding independent of the level of algebra.  Look at statistics if you want a mathematical example.  We fully expect that students who love traditional algebra will balk at the course approach because it asks new things of them, something we often see with traditionally strong students in statistics classes.  Being good at symbolic manipulation does not imply strength with reasoning and problem solving.  Our goal is to have students who can exemplify both.  Again, this is not the Math Wars.  Skills matter but conceptual and applied reasoning do too.

3        The instructional design makes the student a participant, not a spectator.
The authors in Academically Adrift say that faculty need to be approachable to students and connect with them beyond the classroom.  They should also connect with students in other ways than lecture in the classroom.  One of the main premises of MLCS is to not just change what we teach but how we teach it.  Using context, theoretical examples, news articles, cartoons, and case studies, we’re going to teach students to work together and solve problems.  Not everything is truly “real world” but that’s ok. Some things are just food for thought but done differently than we usually do.  For example, instead of saying, “for all real numbers a and b, the commutative property of multiplication says that ab = ba,” we’ll ask “when does order matter and when doesn’t it?”  The commutative property will be defined and explained but so will a lot of other interesting ideas related to operational order. 

There will be direct instruction when we get to points in which the students need and want an explanation so they can move forward.  But we’re not starting with the theory.  We’re doing it when we need it, when it’s cumbersome to not have a method that’s more efficient or a word for what we’re doing.  Give students an interesting problem first and guide them productively through it, still allowing for that uneasiness that comes with confusion and learning, and let them ask what they want to know.  They’ll get to the points we want and at that point, teaching the theory makes sense.

The methods of effective collaborative work are ones that are endorsed by the National Science Foundation and employers everywhere.  If our students are not already employed, they likely will be at some point.  And in that job, they’re going to need to work with another person or persons effectively.

Teaching this way takes skill and is new to many, even seasoned, effective instructors.  It’s different to step aside and let students take the reins for a little while.  Mind you, we’re not saying let them teach the course or never have the instructor in the front of the room.  We’re saying hand over some time to productive problem solving during class that you’re not directly leading all the time.  How much time depends on the teacher and class. 

Because this is a new approach, we’re planning the pilot very intentionally and creating means to make changes and note what’s working or not.  I’ll be attending Heather’s class and she’ll be attending mine.  We’ll be videoing the class as well.  And throughout, we’re
keeping a master binder of the content with notes of how students responded, what needs changing, and what needs more of whatever (time, explanation, etc.).  Following the pilot will be the process of building detailed instructor resources.  Not just answers to problems and sample tests but samples of student work, videos of classes, rubrics for grading, and approaches to sequencing and teaching the content.  Some teachers need all of these, some need none, others are in the middle.  Whatever the needs, we want to satisfy them. Because ultimately, we want this course to have the potential to be taught by any faculty member, experienced or novice, adjunct or full time.


The hope is that we connect with students in and out of the classroom and that they connect with us and their peers.  The great opportunity of this course is that many students taking it will be at the very beginning of their college careers.  They’re not just unprepared for math; they’re unprepared for college.  We can take that opportunity to build skills related to math and college (called college knowledge) as well as support structures that will help them be successful in future classes.  In essence, if they can learn that their instructor and peers are part of the learning equation, they’re more likely to go to those resources when they start to struggle instead of flailing or leaving when the going gets tough.  In the book, the authors claim that students who experience a greater level of learning are more likely to persist when things are difficult.

We hope that these measures along with lessons learned from redesigning the traditional developmental math courses will combine to make a successful new experience for all of us.  And if not, like Edison, then we’ll have at least found at least one method that does not work.  And also like Edison, we’ll keep working until it does.

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