Dr. Paul Nolting's Academic Success Press Blog: A Publication Dedicated to Math Success
Dr. Paul Nolting's Academic Success Press Blog: A Publication Dedicated to Math Success
As promised, here is Part One of our interview with AMATYC's Jack Rotman! A developmental math teacher for more than forty years, Rotman has worked with AMATYC in various positions since 1987. He currently runs the New Life Project—"a national effort to develop a new model for developmental mathematics."
This first portion of our conversation covers many topics, but we mostly speak about his response to Complete College America's infamous "Bridge to Nowhere" findings, as well as Rotman's thoughts on the joys and pleasures of mathematics. Part Two—scheduled to run this Wednesday—focuses predominately on the New Life Project. Note that we spoke with Rotman before AMATYC 2015.
For more on Rotman's thoughts about the "Bridge to Nowhere," click on this link, which will take you to an AMATYC powerpoint presentation that addresses the topic.
ASP Blog: At AMATYC 2015, you plan to give a speech that directly responds to Complete College America's assertion that developmental math (and all remediation) serves as a "bridge to nowhere." What compelled you to respond?
Rotman: It is risky that they are using data to backup predetermined positions. It’s a pretty awful use of data. Overall, the data does show problems; however, I don’t know about all developmental education, but certainly in mathematics, [this bad data is not caused by] nature but by design. Many developmental courses are simply copied from elsewhere and then misused. Our work [at AMATYC] is all about deciding what students actually need at the college level—whether its mathematics, science, or technology, then building courses from these things rather than merely copying a high school course and calling it good enough for college.
One of the things they say in “The Bridge to Nowhere” report is that students come to college expecting college level courses not high school courses—well, I actually agree with that. It is important to give students the college experience, even if they need to do something prior to normal college work. So, our courses are at a somewhat higher level cognitively than traditional developmental math courses. This is one of the problems that we see in our traditional work—it is so procedural and memory based that students don’t get any preparation for the bigger challenges they face in college-level work.
ASP Blog: I know another thing you are passionate about involves the math teachers themselves. We focus so much on students—and justifiably so—that sometimes we don't stop to think that teachers might do a better job if they too were genuinely engaged with the content they teach. Can you discuss this?
Rotman: One of the things I used to work on was getting mathematicians excited about teaching mathematics. The traditional work in college—especially in developmental and college algebra—has been ruined in some ways. It isn’t as exciting as many professionals want it to be. You want to teach something you feel good about—not simply trinomials or how to solve an eight-step rational equation. Those are things we want students to be able to do when needed, but they are not things that make teachers wake up in the morning and say, “Oh, I can’t wait to teach that today.”
The human mind is naturally curious about how things fit together. It’s not that we have to convince students that mathematics is interesting or not interesting. If we present something that we are genuinely excited about—most students respond to that. Right now, it is hard for students to get excited about traditional curriculum because it is the same stuff that they had before that wasn’t useful the first time they saw it.
ASP Blog: So you are saying that teachers need to get excited about their work and students need to better understand the context of what they are learning?
Rotman: This is difficult to articulate accurately. Some people hear me talk and come away thinking, "Jack is all for teaching everything within context.” Other people hear me talk, and they think I’m saying that context is irrelevant. The truth is somewhere in between.
My own background isn’t so much in mathematics as it is in educational psychology. I’ve been reading research for forty years. In all of that reading I’ve never seen any research that shows teaching math in context actually improves learning—it improves motivation, but it can actually harm learning if you are not careful. That is true for most things that we do. It is easier to harm learning than it is to enable it.
When people teach fully from context, they often limit the mathematics they teach to what students can understand at that specific time. I feel really bad about that because if I can’t get a student at least interested in learning mathematics for its own sake, I haven’t shown them what a mathematician is, I’ve just showed them how you use mathematics. These are not the same thing.
When students pass through one of my math classes, I want them to at least get an inkling that the material is something that somebody gets interested in by itself. Even if we can’t apply it right now, this math is something that can be fun for the next sixteen weeks.
I like context—but I never stay there very long. I start with context in my classes—I usually teach something simple, then bring it into context, then go into something more mathematical. This involves a kind of a dance around context, not a long term stay.
ASP Blog: That is so interesting! I can see how someone who is passionate about math, someone who genuinely finds it fun, would almost resent the idea that math is some sort of pill hidden in peanut butter that one tries to force down the throat of a sick dog. If you genuinely care about math, I can see how this approach might come across insulting.
Rotman: Mathematics has always been this amazing and awkward mixture of practical and unpractical. The interesting thing is that some math that was useless twenty years ago is now a matter of national security or enables a business to survive or enables a company to produce something. Today’s useless mathematics is tomorrows economy. You never know.
So do we really want to say to students, “I am only going to teach you what you can use today, which is actually what you could have used two years ago.” We are never completely up to date. When they need something in five years, students will have no idea what they should be looking for.
When people think of math, they usually think only of arithmetic then useless things that don’t apply to life. [This binary] bothers me a lot. History is full of mathematics being embedded in practical things as well as being an abstract pursuit for its own merit. That’s true for most sciences—all of them are like that. The arts too. There are two dimensions in math. You can’t teach just one and lose track of the other.
ASP Blog: You’ve basically just described a paradox. Math is perpetually useful and un-useful—and neither of these categories is fixed.
Rotman: Right. The whole world is a paradox in some ways, from top to bottom. There are days that everything makes sense, but more often than not, there are things that don’t quite fit together.
Click here for Part Two.
Good morning readers! Today, we want to update you about what you can expect to see on the blog in the upcoming weeks. Then we'll pass along a few interesting links to recent stories from around the Web involving developmental mathematics.
1. On Monday, Nov. 30 we will run an interview with Jack Rotman (AMATYC). Not only do we discuss math redesigns in the conversation, but we also talk about the reputation of math itself. Is math something students should "just get over with?" Are real world applications necessary to truly make mathematics valuable to students? We talk about this and much more.
2. We also have upcoming interviews with Rebecca Goosen and Barbara Illowsky. Stay tuned!
1. An interesting piece from Mercer County Community College's student newspaper. The story discusses the headaches of implementing computer-based programs into redesigned classrooms. Spoiler alert! Some of the students are a bit frustrated (shocking, we know)!
2. Another extremely interesting read about the efforts of a few NC State professors to find new and innovative ways to teach math. It is always exciting when math departments receive grants to conduct this type of research. Good luck to all involved!
Good morning readers! The Washington Post, yesterday, published an article on its website that featured a really interesting post from the City University of New York's Math Blog. Written by Jonathan Cornick last April, the piece describes the author's experiences teaching developmental math and college algebra courses. In his effort to find out how, exactly, his friends and family use math in their everyday lives, Cornick grapples with the now age-old debate over the necessity of college algebra. He also briefly explains CUNY's recent experimentation with Carnegie's Statway and Quantway designs. The teacher then provides what he believes to be the answer for students struggling with algebra:
I believe that we must continue to design and implement alternative pathways in mathematics to better serve the students who traditionally get stuck in remediation; Either through alternative remediation, or preferably in mainstreaming those students into an existing credit-bearing Quantitative Reasoning or Statistics course with extra support for their basic skills. These courses should be supported by proven pedagogy and contextualization of the topics.
Here is a link to the original article: http://cunymathblog.commons.gc.cuny.edu/2015/04/24/math-you-use/
It is definitely worth a read.
Hello! For today's post, we wanted to update our readers on Paul's schedule for AMATYC 2015. In addition to manning the Academic Success Press Booth (#311), Paul will also give a presentation titled: Integrating Math Study Skills: Classroom, Modular, and Online Approaches. The presentation is scheduled for Saturday between 10:30 and 11:45 a.m. For more information, see the promotional material below.
This workshop demonstrates how to integrate math study skills into classroom, modular, emporium, and online courses by teaching students reading, homework, memory, note-taking, test-taking, anxiety reduction and motivational skills. It will also help faculty learn how to use modern technology, including phone and tablet applications, to help their students become better independent learners. The discussion will then move on to our new Academic Success Press math success blog, which features numerous interviews with national experts, including many who will present at the NADE/AMATYC National Math Summit in March. The blog is intended to establish a meeting ground for those working in the world of mathematics education. It features articles on recent events, research, and prominent individuals in the field. (continued on back of page)
Hello readers! Today we present a brief interview with Dr. Rochelle Beatty. Beatty, who has worked for years both in the academic and publishing worlds, is currently teaching a few math courses at a community college in Kansas. Because we have spoken with so many administrators and researchers in recent weeks, we thought we'd mix things up a bit and try to capture the teachers' perspective on study skills and math redesigns. Enjoy!
ASP Blog: I want to start by asking you about the importance of math-specific study skills, specifically for first-year students or students in developmental mathematics. How important is it that students learn and use these skills in their first college-level math courses?
Beatty: Very important. If students come into college unprepared, then they need not only instruction on the content of a class, but also on how to study—because this is usually one of the main reasons they are unprepared: they've just never had a grasp on study skills. This includes simple things like knowing how to take notes or understanding the importance of being in class. The easiest thing you can do to ensure a good grade is to show up. It seems like sometimes this is the biggest challenge with our developmental math students—their lives just keep getting in the way. All of this falls under study strategies: knowing how to manage your time, knowing how to prioritize school so that your studies are always at the forefront of your life.
I really think that—with a lot of redesign models moving to computer-based modes of instruction—study skills become even a bigger part of the picture. Students need to be able to archive their work on paper, so that they can go back and reflect upon what they’ve done and not only on what they’ve seen.
ASP Blog: On that topic, what specific skills do online or emporium model students need?
Beatty: Again, time management is particularly important in this setting. Students are not going to make it through a course if they think that their computer lab time is the only time they need to be engaged with class content. It still holds that students need to study three hours outside of class for every one hour in class. In fact, I just told my students yesterday: “Don’t just think that those three hours are going to happen on their own. You have to set a schedule, and it probably isn’t a good idea to devote these three hours to the night before class in a single chunk, because your mind is easily fatigued. So you have to make sure you have one hour somewhere during the day to go back and study your math and keep progressing on it.”
The other thing I tell students is that the Internet they find on campus might be some of the best Internet around in terms of speed and having instructional and technical support. So they should always make sure they schedule at least one additional hour of computer time between classes somewhere on campus.
ASP Blog: In terms of computer skills: one would assume that modern students would have grown up with computers and therefore have a basic grasp on how to use them. But this isn’t always the case, correct?
Beatty: Sadly, although our students are extremely connected to their gadgets—and have anxiety when they are without these gadgets—this does not mean that knowing how to use those things for everyday life is equivalent to knowing how to use those devices for educational or instructional usage. You really do need to know where your students are [in this regard] and make sure you can provide them keyboarding skills and other traditional computer skills they might not have.
Not only do you need to teach math, but you need to teach computer proficiency. Sometimes these skills are not always intuitive—even with something simple like printing documents. There are so many other things that come into play also. With their phones and gadgets students aren’t having to save files or take screenshots. If you are teaching an online or emporium model course, you really need to be hands on in the classroom.
ASP Blog: How important is it that teachers read up on new pedagogy—new ideas, new discourse, being published in academic journals?
Beatty: I think it is huge. For instance, I think that if teachers don’t understand the difference between how a developmental math student processes information versus how a college-level student processes information, they can’t properly serve either group. The same is true if you don’t understand adult students and their learning preferences versus traditional students and their learning preferences. There is a lot of theory out there that I think instructors should not only be aware of, but also incorporate into practice.
ASP Blog: You wrote your dissertation on cognitive development and vocabulary. Do you use this research in your classroom?
Beatty: Yes. Specifically vocabulary. In mathematics, understanding what certain words mean and understanding how one set of directions differs from another set of directions can really be a make it or break it situation for students. Students must make vocabulary a priority, which once again goes back to study skills.
Cognitive development is also important. Students have to grow from a perspective that math is dualistic—right/wrong, black/white, true/false—to a perspective that math is multiplistic—that there is not just one way to solve a problem, one way to pose an answer. Students should not erase their work just because their path is different from one of their classmate's. Students need to know how to let that point of confusion be an easy thing to accept while one waits for the inevitable “Aha!" moment—when they realize, "we both got the same answer, we just went about it differently.”
I think this is another place where developmental students often struggle—often because past high school instructors insisted that work only be completed by using a very uniform approach, and now their college instructor uses an entirely different method. In the classroom, we need to not only focus on the content, but also make sure that our students embrace this notion that math doesn’t always have to start the same way—that you have to look at a problem and decide between all of the different methods you have at your disposal.
Welcome back! Today we present the final section of our talk with the Carnegie Foundation's Director of Productive Persistence: Rachel Beattie! This particular portion of our conversation centers on the testing and application of new strategies in the classroom. The Carnegie Foundation, one of our nation's most prominent educational research centers, has developed a fascinating model for applied research, and Rachel does an amazing job here breaking down exactly what teachers should and should not do when conducting research or applying new strategies in class. Enjoy!
ASP Blog: Moving on to the next topic, will you talk a little bit about the non-cognitive factors that affect students while they are learning math?
Beattie: Sure! This could easily turn into quite the list, as it really is a complex landscape—all of the different factors that affect math learning.
Once again, the knowledge that intelligence is malleable and not fixed is really important. When talking with students, I often hear them talk as if there are two races of people: math people and non-math people. We want students to see that this isn’t really the case. This is usually an uphill battle. Over two-thirds of our students answer this way. For students in developmental mathematics, you can probably guess which group they think they are in. That is why we make sure our pathways address productive persistence—to make sure students think about creating new mindsets.
But we also believe that many other non-cognitive factors are important: belonging being one of the biggest. The sense that one belongs in a math course is incredibly predictive of math success. It is really a problem in math because of all of the negative stigmas and stereotypes attached to mathematics learning—that girls, for instance, can’t learn math. Even positive stereotypes present problems.
The point is that if you believe that others are judging you, or that stereotypes dictate that your classmates don’t think highly of you, this can drastically change your feelings about your ability to succeed in a particular setting. You might constantly question whether or not you belong—especially if something negative happens [in class].
Emotional regulation is another main non-cognitive factor. What is really bad here is how we sometimes mistake stress—sometimes your body has the same physiological reaction to things you want to approach as it does to things you want to run away from: heart-beating, sweaty palms, intake of oxygen, all of these are related to both of these reactions. So what we do is have students replay these physiological reactions and test their bodies’ ability to get ready for stress. We have seen that this significantly improves performance on exams—it doesn’t help students develop better study strategies—but it does reduce anxiety enough to help students perform better on exams.
The last factor I’ll bring up is homework systems. We want students to become self-regulated learners. We actually build in opportunities for students to practice these self-regulating skills directly within their homework. This helps students increase confidence in their knowledge of how to accomplish the task at hand. We also make sure that homework assignments always build in complexity and are applied in different situations. This is really essential to students becoming experts. It also helps students keep engaged.
Reflection is another major part of self-regulated learning—so we also include a phase after each homework assignment for students to reflect on the strategies they used and any next steps they want to take. Many of our students, in the past, have only learned shallow study and homework strategies. We want to create an environment in which they can flesh out their meta-cognitive skills.
ASP Blog: It seems like you are very much in the business of applied psychology. You use whatever you can figure out about the way people think and learn and apply this knowledge directly into the classroom. What is interesting about this to me is that one both learns and applies information in the same exact setting: the classroom. How can universities use the classroom as a test case, while still not losing focus on the main function of the class itself: teaching math?
Beattie: That is a great question. Our goal is to never interfere with the teaching of mathematics. For this reason, we use a methodology called “improvement science.” This involves small paths of change, not huge overhauls. The goal is to conduct tests that do not take more than ten minutes or so from a class. It is based upon six different principles.
1. You should be user-centered and focused. You really listen to students’ questions and concerns, and you are extremely focused in on a direct problem.
2. Next, you really need to attend to students’ abilities. We want to understand what works for whom, and under what conditions. Across our pathways, there has never been this “one-size-fits-all” mentality. There are adaptations that people need to make, in terms of setting, for something to work.
3. It is really important that if you do make a change, you figure out how this change interacts with everything else in your particular setting—otherwise whatever you are trying to apply might become overwhelming.
4. We also document what we learn. What are my hypotheses, what are my learning questions? What is my data? This helps you to reflect on an action afterwards and prepare for the next test. We can’t improve what we can’t measure.
5. You don’t just want to look at test scores. You want to take note of the everyday behavior in the classroom: are students turning in their homework, are they asking questions, how are groups working? In order to improve a classroom, you really need to understand what is happening there every day.
6. We help create what we call Network Improvement Communities to make sure faculty, teachers and students are working together. Creating a networked community keeps you from having to do everything yourself. If everybody is working together, then someone might have already tried something that will work well in your particular setting—they have already tested it out, and it just needs to be adapted a bit.
All of this helps to really reduce the load of testing so that it doesn’t seem too unwieldy.
ASP Blog: Can you talk a little bit specifically about how to properly measure strategy results within a classroom?
Beattie: Outcome measures are always really important, so I don’t want to say never measure your outcomes—but you do want to look at the larger goals and aims of your project. If your goal is to improve success in one math classroom, then you definitely want to look at grades, as well as the credits students get in mathematics after that class. At the whole college level, you want to look across your whole department: grades, credits, transfer rates, etc.
With outcome data, you want to make sure it closely mirrors your aims: why you are doing this work in the first place?
What is really important for our work is what we call “process measures.” These actually measure the process of improvement, the daily processes in class. For us, attendance is a big one. We have developed a couple processes that we know work because we measure them daily. We were able to meet semester long attendance rates between 85 percent and 93.3 percent with just one small change that we tried out. So it is really powerful to put these day-to-day measures to work. Another one we look at is group functioning. Are students being supported in their groups, do they feel like they are being productive and that everyone is contributing? That is really important to form a community.
You also want to look at “balancing measures.” Sometimes changes unintentionally affect classroom learning—I love that you already brought up time, that new strategies take up a lot of faculty members’ time and keeps them from doing other things that were already affective. This means that it is important to think about “if I do this change, what might be affected in my classroom either short term or long term and how can I measure that?”
Finally, another part of our data collection system is what we call “practical measures.” It is hard to measure a student’s mindset in three minutes. If you are familiar with psychological research, we aren’t big on short test batteries. Questionnaires and interviews are always LONG, because you really want to explore the contextual frameworks, you want to understand students’ beliefs on multiple levels. However, with a practical measure, you have to cut it down drastically and really focus in on the variables that are causally related to student success. With practical measures, we measure students at week one and week four, only because we do a lot of intervention and we are setting up a lot of classroom norms and expectations—this allows us to measure a before and an after. It is really wonderful to see [this dynamic] in our data system, because it helps us understand the different elements that lead to student success. This is true from our point of view, but also our faculty’s. We actually give each of our faculty members a report about their classrooms and about productive persistence. This gives them classroom aggregated data on individual and group mindsets—on how well students are transitioning.
And that' wraps it up! Once again, we want to thank Rachel Beattie and the Carnegie Foundation for their participation. Tune in next Monday for another exciting post!
ASP Blog: Do you want to tell us a little about your background?
Beattie: Sure! My background is in psychology. When studying for my Ph.D., I specifically focused on the etiology of learning differences in mathematics [with regards to] reading and language—with a heavy focus on dyslexia and specific language impairments. I wanted to understand why these learning differences came to be and what the actual differences were between typical and atypical reading and language processing in mathematics. While I was doing that, I was also an adjunct professor at Occidental College and USC. After I finished my Ph.D., I taught research methods, statistics, learning and memory courses, and I helped TA a course on the science of happiness. I then went to Ohio State University where I did my postdoctoral fellowship in neuroscience, which involved conducting neuroimaging on children and adults related to their mathematics reading and language processes. This gave us great insight into the development of these differences.
After my postdoc, what I really wanted to do was get away from research about the basic processes, and get more into applied research—actually helping students and teachers in their classrooms during the school year. So, I started working at the Carnegie Foundation. I’ve been here for a year and a half now, and it has been really wonderful to actually make a practical difference on a daily basis.
ASP Blog: Can you talk a little bit about the variables that predict math success?
Beattie: Sure. I’ll speak mostly on developmental mathematics because that is the data I am working with right now. Obviously, one of the biggest variables is the foundational mathematics skills that students come to a course with—we actually measure these when students come in with a conceptual knowledge quiz. This is a pretty strong predictor, though it is not necessarily deterministic. There are other factors that we see that are really important as well. We see that students’ mindsets about their ability to perform and learn in a classroom are also predictive. We also often see that a student’s certainty of his or her belonging in the classroom is important. If he or she has high learning uncertainties, then we see that they are much more likely to withdraw—and if these same students finish a course, they usually have a lower score at the end.
Anxiety is another interesting variable in the data. Research is showing us more and more that very low and very high anxiety are maladaptive. Very low anxiety is actually negatively predictive of success. It is very linear too, as we see that high anxiety is actually a predictor of success—we think this is because these students are putting in more effort outside of the classroom. That is our current working theory, though we are still puzzled a bit about that.
Also, in the pathways, we do a lot of intervention around students mindsets and beliefs. Intriguingly, we see that their week one beliefs are no longer predictive of course outcomes. When we started we saw that, yes, they were very predictive to these mindsets, uncertainties, stereotypes, and anxiety. However, now we see that week four is much more predictive of success than week one. This suggests that we have shifted students’ mindsets. It is really nice to see. We always want to create a learning environment, a culture, where your belief sets at the beginning are irrelevant. It is how you perform throughout the class that is what is ultimately important to your success.
ASP Blog: Interesting! How much of this is the result of students better understanding what is expected in a class and having a better grasp on whether or not they have what it takes to find success in the course?
Beattie: I’m sure that is part of it. We see that students are more comfortable asking questions by [week four]. A lot of it, though, is the actual interventions we conduct to help students see themselves as capable mathematics learners. It is important to shift student thinking and self-perceptions in that way.
ASP Blog: Which is a perfect segue into your personal expertise: productive persistence—the ability for a student to persevere through difficult times or even learn how to handle success. Do you want to talk a little bit about this behavior?
Beattie: Of course! My favorite subject! People always ask me what “productive persistence” means. We think of it as how students continue to put forth effort during challenges. When they do so we hope they are using affective strategies. We focus on productive persistence because in our data we are seeing a lot of students being unproductively persistent. We don’t want students coming back to the same courses over and over again. They know the course is important and that they need it in order to pursue their dreams. But they aren’t succeeding; they aren’t being consistently productive.
We want to help create environments that allow students to be productively persistent in mathematics. When we develop frameworks, we introduce students to faculty, we consult with psychological literature, as well as with general education reform literature, and we form a network of faculty members and researchers to create frameworks based on all of these sources of information. [During this process] we came up with nearly `100 possible constructs that might contribute to productive persistence, and we narrowed these down to five high-leverage factors. If we make real movement on these five, we will help students become more productively persistent.
While there are many things that affect productive persistence, we focused on the following five because they are within our locus of control:
1. That students believe they are capable of learning. They believe it is possible to succeed in a course.
2. It is really important for students to develop social ties to peers, faculty, and the course. If anything happens that makes students wonder if they belong in a classroom setting, they often take this on as their identity within the classroom.
3. That students see a course has value. When we talk about value, we mean that students are able to relate material to their short-term and long-term interests.
4. We want students to know how to succeed in a college setting. This involves traditional study skills, cognitive study skills, but also emotional recognition skills and general college-know-how skills: how to navigate a syllabus, knowing how to navigate course progression, etc.
5. We want to help support faculty to help students to develop these mindsets and skills. We believe that we are in the business of shifting student perceptions, but also that it is important to change the learning environment. There needs to be a congruency between the mindsets we are helping students develop and the environment in which they are learning.
We also want to create an effective pathway through college math. We actually created a curriculum that engages students in math that matters—so it involves real life problems, so that students can see the relevance of mathematics in their lives. To support all of that, we have a lot of support for faculty built into the classrooms, we have faculty mentorship, we have online resources, and a lot of this focuses on productive persistence. The pedagogy again supports productive persistence because it promotes collaborative learning. We focus on activities that involve students working with one another to better understand the concepts of mathematics. We don’t just want them to have the procedural skills; we want them to have the conceptual knowledge too.
I think productive persistence works really well as a part of this whole structure. We want the whole environment, the pathways of developmental mathematics, to support students to develop the right mindsets and skills.
That wraps up Part One! Part Two continued, here.
On July 26, the Washington Post published an interesting article regarding entrance exams and remediation. Given the tenor of our last post, which recapitulated an article in the Journal of Developmental Education that advocated the reform not replacement of assessment tests, we thought we'd pass along information on a different approach being taken by Montgomery College in Maryland.
The entire article is interesting—though we may quibble a bit with a few of its major points. While well-intentioned, the educators interviewed in the piece make the same basic argument leveled by comparably ardent anti-remedial forces. Rather than recognizing and fixing flaws within the developmental education system, they are putting more of an emphasis on avoidance, as evidenced in the quote below:
Instead of relying on standardized test results, the pilot program also looks at high school transcripts. If students earn an A or B in Algebra 2, for example, they might be allowed to move into college-level math. If students earn similar grades in advanced placement or honors English and world history, they might be able to go into college-level English.
This in itself is not necessarily a bad idea. Still, one has to wonder, how are these students going to perform when placed directly into college-level math courses? Let's say these same students who got an A or B in Algebra 2 took said course their junior year of high-school. After not taking a math course for more than a year, are they still prepared to take the hardest math course in which they've ever enrolled?
The answer to this question certainly remains up for debate.
The Challenges of Assessment and Placement: Thoughts on Saxon and Morante's 2014 Study for the Journal of Developmental Education
Hello readers! Happy Monday! For our first post this week, we want to turn your attention to an interesting article, which ran in the Winter 2014 edition of the Journal of Developmental Education. Written by D.P. Saxon and E.A. Morante, "Effective Student Assessment and Placement Challenges and Recommendations" explores the challenges of student assessment and placement methods within the greater structure of modern developmental education redesign movements. It also provides a few recommendations for what its authors deem “common inadequacies in college assessment and placement processes.”
The authors begin by arguing that placement exams are extremely important to first-year college students. They state plainly that making sure students wind up in the correct courses is crucial to their future success. Citing a study by Hunter Boylan, they contend that research proves mandatory assessment and placement exams are effective, assuming institutions have already established evidence that their developmental courses and instruction are “quality” attributes.
With this in mind, many challenges remain. To begin with, the authors say, “No test gives an absolutely exact measure of skills or any other variable.” Worse, many of these tests fail to include “other measures.” This is particularly true of affective characteristics, which the authors point out account for nearly 41% of a student’s grade. These characteristics—which included prior employment, confidence levels, anxiety, attitude, etc.—typically fall into the realm where “life and college” intersect. This means that affective characteristics tend to place math within the greater context of a student’s life and thereby become very important for their future success (particularly for first-year college students taking their first college-level math course).
The authors also point out that many institutions suffer from inadequate and low-performing advising systems, while others often fail to enforce mandatory placement policies. In the end, they suggest that institutions—particularly those in the middle of large-scale redesigns—should take a series of steps to ensure success. Colleges should help students transition from high school to college, require mandatory assessment and advising for all incoming students, coordinate assessment services, and modify placement tests to directly address skills deficiencies. They should also strengthen bridge programs, use more effective test cut score ranges, and learn to evaluate the placement process systematically.
For more please see:
Saxon, D.P., Morante, E.A. “Effective Student Assessment and Placement Challenges and Recommendations.” Journal of Developmental Education, Volume 37, Issue 3, Spring 2014. Pages 24-31.
Dr. Nolting is a national expert in assessing math learning problems, developing effective student learning strategies, assessing institutional variables that affect math success and math study skills. He is also an expert in helping students with disabilities and Wounded Warriors become successful in math. He now assists colleges and universities in redesigning their math courses to meet new curriculum requirements. He is the author of two math study skills texts: Winning at Math and My Math Success Plan.
American Mathematical Association of Two-Year Colleges presenter, Senior Lecturer-Modular