|Posted on August 14, 2018 at 8:50 AM||comments (0)|
A while back, a faculty member teaching in a community college career program told me, “I don’t need to assess. I know what my students are having problems with—math.”
Well, maybe so, but I’ve found that my perceptions often don’t match reality, and systematic evidence gives me better insight. Let me give you a couple of examples.
Example #1: you may have noticed that my website blog page now has an index of sorts on the right side. I created it a few months ago, and what I found really surprised me. I aim for practical advice on the kinds of assessment issues that people commonly face. Beforehand I’d been feeling pretty good about the range and relevance of assessment topics that I’d covered. The index showed that, yes, I’d done lots of posts on how to assess and specifically on rubrics, a pet interest of mine. I was pleasantly surprised by the number of posts I’d done on sharing and using results.
But what shocked me was how little I’d written on assessment culture: only four posts in five years! Compare that with seventeen posts on curriculum design and teaching. Assessment culture is an enormous issue for assessment practitioners. Now knowing the short shrift I’d been giving it, I’ve written several more blog posts related to assessment culture, bring the total to ten (including this post).
(By the way, if there’s anything you’d like to see a blog post on, let me know!)
Example #2: Earlier this summer I noticed that some of the flowering plants in my backyard weren’t blooming much. I did a shade study: one sunny day when I was home all day, every hour I made notes on which plants were in sun and which were in shade. I’d done this about five years ago but, as with the blog index, the results shocked me; some trees and shrubs had grown a lot bigger in five years and consequently some spots in my yard were now almost entirely in shade. No wonder those flowers didn’t bloom! I’ll be moving around a lot of perennials this fall to get them into sunnier spots.
So, yes, I’m a big fan of using systematic evidence to inform decisions. I’ve seen too often that our perceptions may not match reality.
But let’s go back to that professor whose students were having problems with math and give him the benefit of the doubt—maybe he’s right. My question to him was, “What are you doing about it?” The response was a shoulder shrug. His was one of many institutions with an assessment office but no faculty teaching-learning center. In other words, they’re investing more in assessment than in teaching. He had nowhere to turn for help.
My point here is that assessment is worthwhile only if the results are used to make meaningful improvements to curricula and teaching methods. Furthermore, assessment work is worthwhile only if the impact is in proportion to the time and effort spent on the assessment. I recently worked with an institution that undertook an elaborate assessment of three general education learning outcomes, in which student artifacts were sampled from a variety of courses and scored by a committee of trained reviewers. The results were pretty dismal—on average only about two thirds of students were deemed “proficient” on the competencies’ traits. But the institutional community is apparently unwilling to engage with this evidence, so nothing will be done beyond repeating the assessment in a couple of years. Such an assessment is far from worthwhile; it’s a waste of everyone’s time.
This institution is hardly alone. When I was working on the new 3rd edition of my book Assessing Student Learning: A Common Sense Guide, I searched far and wide for examples of assessments whose results led to broad-based change and found only a handful. Overwhelmingly, the changes I see are what I call minor tweaks, such as rewriting an assignment or adding more homework. These changes can be good—collectively they can add up to a sizable impact. But the assessments leading to these kinds of changes are worthwhile only if they’re very simple, quick assessments in proportion to the minor tweaks they bring about.
So is assessment worth it? It’s a mixed bag. On one hand, the time and effort devoted to some assessments aren’t worth it—the findings don’t have much impact. On the other hand, however, I remain convinced of the value of using systematic evidence to inform decisions affecting student learning. Assessment has enormous potential to move us from providing a good education to providing a truly great education. The keys to achieving this are commitments to (1) making that good-to-great transformation, (2) using systematic evidence to inform decisions large and small, and (3) doing only assessments whose impact is likely to be in proportion to the time, effort, and resources spent on them.
|Posted on July 30, 2018 at 8:20 AM||comments (2)|
I often hear questions about how long an “assessment cycle” should be. Fair warning: I don’t think you’re going to like my answer.
The underlying premise of the concept of an assessment cycle is that assessment of key program, general education, or institutional learning goals is too burdensome to be completed in its entirety every year, so it’s okay for assessments to be staggered across two or more years. Let’s unpack that premise a bit.
First, know that if an accreditor finds an institution or program out of compliance with even one of its standards—including assessment—Federal regulations mandate that the accreditor can give the institution no more than two years to come into compliance. (Yes, the accreditor can extend those two years for “good cause,” but let’s not count on that.) So an institution that has done nothing with assessment has a maximum of two years to come into compliance, which often means not just planning assessments but conducting them, analyzing the results, and using the results to inform decisions. I’ve worked with institutions in this situation and, yes, it can be done. So an assessment cycle, if there is one, should generally run no longer than two years.
Now consider the possibility that you’ve assessed an important learning goal, and the results are terrible. Perhaps you learn that many students can’t write coherently, or they can’t analyze information or make a coherent argument. Do you really want to wait two, three, or five years to see if subsequent students are doing better? I’d hope not! I’d like to see learning goals with poor results put on red alert, with prompt actions so students quickly start doing better and prompt re-assessments to confirm that.
Now let’s consider the premise that assessments are too burdensome for them all to be conducted annually. If your learning goals are truly important, faculty should be teaching them in every course that addresses them. They should be giving students learning activities and assignments on those goals; they should be grading students on those goals; they should be reviewing the results of their tests and rubrics; and they should be using the results of their review to understand and improve student learning in their courses. So, once things are up and running, there really shouldn’t be much extra burden in assessing important learning goals. The burdens are cranking out those dreaded assessment reports and finding time to get together with colleagues to review and discuss the results collaboratively. Those burdens are best addressed by minimizing the work of preparing those reports and by helping faculty carve out time to talk.
Now let’s consider the idea that an assessment cycle should stagger the goals being assessed. That implies that every learning goal is discrete and that it needs its own, separate assessment. In reality, learning goals are interrelated; how can one learn to write without also learning to think critically? And we know that capstone assignments—in which students work on several learning goals at once—are not only great opportunities for students to integrate and synthesize their learning but also great assessment opportunities, because we can look at student achievement of several learning goals all at once.
Then there’s the message we send when we tell faculty they need to conduct a particular assessment only once every three, four, or five years: assessment is a burdensome add-on, not part of our normal everyday work. In reality, assessment is (or should be) part of the normal teaching-learning process.
And then there are the practicalities of conducting an assessment only once every few years. Chances are that the work done a few years ago will have vanished or at least collective memory will have evaporated (why on earth did we do that assessment?). Assessment wheels must be reinvented, which can be more work than tweaking last year’s process.
So should assessments be conducted on a fixed cycle? In my opinion, no. Instead:
- Use capstone assignments to look at multiple goals simultaneously.
- If you’re getting started with assessment, assess everything, now. You’ve been dragging your feet too long already, and you’re risking an accreditation action. Remember you must not only have results but be using them within two years.
- If you’ve got disappointing results, move additional assessments of those learning goals to a front burner, assessing them frequently until you get results where you want them.
- If you’ve got terrific results, consider moving assessments of those learning goals to a back burner, perhaps every two years or so, just to make sure results aren’t slipping. This frees up time to focus on the learning goals that need time and attention.
- If assessment work is widely viewed as burdensome, it’s because its cost-benefit is out of whack. Perhaps assessment processes are too complicated, or people view the learning goals being assessed as relatively unimportant, or the results aren’t adding useful insight. Do all you can to simplify assessment work, especially reporting. If people don't find a particular assessment useful, stop doing it and do something else instead.
- If assessment work must be staggered, stagger some of your indirect assessment tools, not the learning goals or major direct assessments. An alumni survey or student survey might be conducted every three years, for example.
- For programs that “get” assessment and are conducting it routinely, ask for less frequent reports, perhaps every two or three years instead of annually. It’s a win-win reward: less work for them and less work for those charged with reviewing and offering feedback on assessment reports.
|Posted on June 24, 2018 at 4:30 PM||comments (1)|
A recent paper co-sponsored by AALHE and Watermark identified some key professional development needs of assessment practitioners.
While a book is no substitute for a rich, interactive professional development experience, some of the things that assessment practitioners want to learn about are discussed in my books Assessing Student Learning: A Common Sense Guide (new 3rd edition) and Five Dimensions of Quality: A Common Sense Guide to Accreditation and Accountability. Perhaps they’re a good place to kick off your professional development.
Analyzing and Interpreting Assessment Data
See Chapter 24 (Analyzing Evidence of Student Learning) of Assessing Student Learning (3rd ed.).
Analyzing and Interpreting Qualitative Results
See “Summarizing qualitative evidence” on pages 313-316 of Chapter 23 (Summarizing and Storing Evidence of Student Learning) of Assessing Student Learning (3rd ed.)
Reporting Assessment Results
See Chapter 25 (Sharing Evidence of Student Learning) of Assessing Student Learning (3rd ed.) and Chapter 16 (Transparency: Sharing Evidence Clearly and Readily) of Five Dimensions of Quality.
This is such a big issue that the 3rd edition of Assessing Student Learning devotes six chapters to it. See Part 3, which includes the following chapters:
Chapter 9 (Guiding and Coordinating Assessment Efforts)
Chapter 10 (Helping Everyone Learn What to Do)
Chapter 11 (Supporting Assessment Efforts)
Chapter 12 (Keeping Assessment Cost-Effective)
Chapter 13 (Collaborating on Assessment)
Chapter 14 (Valuing Assessment and the People Who Contribute)
A good place to start is Chapter 14, because it begins with a section titled, “Why is this so hard?” Even better, see the chapter that section summarizes: Chapter 4 (Why Is This So Hard?) of Five Dimensions of Quality.
Also see Chapter 17 (Using Evidence to Ensure and Advance Quality and Effectiveness) in Five Dimensions of Quality.
Culture of Change
See Chapter 18 (Sustaining a Culture of Betterment) of Five Dimensions of Quality along with the aforementioned Chapter 4 (Why Is This So Hard?) in the same book. For a briefer discussion, see “Value innovation, especially in improving teaching” on pages 180-181 of Chapter 14 (Valuing Assessment and the People Who Contribute) of Assessing Student Learning (3rd ed.).
Effective/Meaningful/Best Assessment Practices
See Chapter 3 (What Are Effective Assessment Practices?) of Assessing Student Learning (3rd ed.) and Chapter 14 (Good Evidence Is Useful) of Five Dimensions of Quality.
Co-Curricular Learning Outcomes and Assessment
Information on co-curricula is scattered throughout the new 3rd edition of Assessing Student Learning. See the following:
“Learning goals for co-curricular experiences” on pages 57-58 of Chapter 4 (Learning Goals: Articulating What You Most Want Students to Learn)
“Planning assessments in co-curricula” on pages 110-112 of Chapter 8 (Planning Assessments in Other Settings)
Chapter 20 (Other Assessment Tools)
Chapter 21 (Assessing the Hard-to-Assess)
See Chapter 15 (Designing Rubrics to Plan and Assess Assignments) of Assessing Student Learning (3rd ed.).
See Chapter 22 (Setting Meaningful Standards and Targets) of Assessing Student Learning (3rd ed.) and Chapter 15 (Setting and Justifying Targets for Success) of Five Dimensions of Quality.
See Chapter 20 (Program Reviews: Drilling Down into Programs and Services) of Five Dimensions of Quality.
|Posted on May 2, 2018 at 6:55 AM||comments (0)|
I look on learning goals as promises that we make to students, employers, and society: If a student passes a course or graduates, he or she WILL be able to do the things we promise in our learning goals.
But there are some things we hope to instill in students that we can’t guarantee. We can’t guarantee, for example, that every graduate will be a passionate lifelong learner, appreciate artistic expressions, or make ethical decisions. I think these kinds of statements are important aims that might be expressed in a statement of values, but they’re not really learning goals, because they’re something we hope for, not something we can promise. Because they’re not really learning goals, they’re very difficult if not impossible statements to assess meaningfully.
How can you tell if a learning goal is true learning goal—an assessable promise that we try to keep? Ask yourself the following questions.
Is the learning goal stated clearly, using observable action verbs? Appreciate diversity is a promise we may not be able to keep, but Communicate effectively with people from diverse backgrounds is an achievable, assessable learning goal.
How have others assessed this learning goal? If someone else has assessed it meaningfully and usefully, don’t waste time reinventing the wheel.
How would you recognize people who have achieved this learning goal? Imagine that you run into two alumni of your college. As you talk with them, it becomes clear that one appreciates artistic expressions and the other doesn’t. What might they say about their experiences and views that would lead you to that conclusion? This might give you ideas on ways to express the learning goal in more concrete, observable terms, which makes it easier to figure out how to assess it.
Is the learning goal teachable? Ask faculty who aim to instill this learning goal to share how they help students achieve it. If they can name specific learning activities, the goal is teachable—and assessable, because they can grade the completed learning activities. But if the best they can say is something like, “I try to model it” or “I think they pick it up by osmosis,” the goal may not be teachable—or assessable. Don’t try to assess what can’t be taught.
What knowledge and skills are part of this learning goal? We can’t guarantee, for example, that all graduates will make ethical decisions, but we can make sure that they recognize ethical and unethical decisions, and we can assess their ability to do so.
How important is this learning goal? Most faculty and colleges I work with have too many learning goals—too many to assess well and, more important, too many to help students achieve well in the time we have with them. Ask yourself, “Can our students lead happy and fulfilling lives if they graduate without having achieved this particular learning goal?”
But just because a learning goal is a promise we can’t keep doesn’t mean it isn’t important. A world in which people fail to appreciate artistic expressions or have compassion for others would be a dismal place. So continue to acknowledge and value hard-to-assess learning goals even if you’re not assessing them.
For more information on assessing the hard-to-assess, see Chapter 21 of the new 3rd edition of Assessing Student Learning: A Common Sense Guide.
|Posted on March 13, 2018 at 9:50 AM||comments (3)|
In my February 28 blog post, I noted that many faculty have been expressing frustration that assessment is a waste of an enormous amount of time and resources that could be better spent on teaching. Here are some strategies to help make sure your assessment activities are meaningful and cost-effective, all drawn from the new third edition of Assessing Student Learning: A Common Sense Guide.
Don’t approach assessment as an accreditation requirement. Sure, you’re doing assessment because your accreditor requires it, but cranking out something only to keep an accreditor happy is sure to be viewed as a waste of time. Instead approach assessment as an opportunity to collect information on things you and your colleagues care about and that you want to make better decisions about. Then what you’re doing for the accreditor is summarizing and analyzing what you’ve been doing for yourselves. While a few accreditors have picky requirements that you must comply with whether you like them or not, most want you to use their standards as an opportunity to do something genuinely useful.
Keep it useful. If an assessment hasn’t yielded useful information, stop doing it and do something else. If no one’s interested in assessment results for a particular learning goal, you’ve got a clue that you’ve been assessing the wrong goal.
Make sure it’s used in helpful ways. Design processes to make sure that assessment results inform things like professional development programming, resource allocations for instructional equipment and technologies, and curriculum revisions. Make sure faculty are informed about how assessment results are used so they see its value.
Monitor your investment in assessment. Keep tabs on how much time and money each assessment is consuming…and whether what’s learned is useful enough to make that investment worthwhile. If it isn’t, change your assessment to something more cost-effective.
Be flexible. A mandate to use an assessment tool or strategy that’s inappropriate for a particular learning goal or discipline is sure to be viewed as a waste of everyone’s time. In assessment, one size definitely does not fit all.
Question anything that doesn’t make sense. If no one can give a good explanation for doing something that doesn’t make sense, stop doing it and do something more appropriate.
Start with what you have. Your college has plenty of direct and indirect evidence of student learning already on hand, from grading processes, surveys, and other sources. Squeeze information out of those sources before adding new assessments.
Think twice about blind-scoring and double-scoring student work. The costs in terms of both time and morale can be pretty steep (“I’m a professional! Why can’t they trust me to assess my own students’ work?” ). Start by asking faculty to submit their own rubric ratings of their own students’ work. Only move to blind- and double-scoring if you see a big problem in their scores of a major assessment.
Start at the end and work backwards. If your program has a capstone requirement, students should be demonstrating achievement in many key program learning goals in it. Start assessment there. If students show satisfactory achievement of the learning goals, you’re done! If you’re not satisfied with their achievement of a particular learning goal, you can drill down to other places in the curriculum that address that goal.
Help everyone learn what to do. Nothing galls me more than finding out what I did wasn’t what was wanted and has to be redone. While we all learn from experience and do things better the second time, help everyone learn what to do so, their first assessment is a useful one.
Minimize paperwork and bureaucratic layers. Faculty are already routinely assessing student learning through the grading process. What some resent is not the work of grading but the added workload of compiling, analyzing, and reporting assessment evidence from the grading process. Make this process as simple, intuitive, and useful as possible. Cull from your assessment report template anything that’s “nice to know” versus absolutely essential.
Make assessment technologies an optional tool, not a mandate. Only a tiny number of accreditors require using a particular assessment information management system. For everyone else, assessment information systems should be chosen and implemented to make everyone’s lives easier, not for the convenience of a few people like an assessment committee or a visiting accreditation team. If a system is hard to learn, creates more work, or is expensive, it will create resentment and make things worse rather than better. I recently encountered one system for which faculty had to tally and analyze their results, then enter the tallied results into the system. Um, shouldn’t an assessment system do the work of tallying and analysis for the faculty?
Be sensible about staggering assessments. If students are not achieving a key learning goal well, you’ll want to assess it frequently to see if they’re improving. But if students are achieving another learning goal really well, put it on a back burner, asking for assessment reports on it only every few years, to make sure things aren’t slipping.
Help everyone find time to talk. Lots of faculty have told me that they “get” assessment but simply can’t find time to discuss with their colleagues what and how to assess and how best to use the results. Help them carve out time on their calendars for these important conversations.
Link your assessment coordinator with your faculty teaching/learning center, not an accreditation or institutional effectiveness office. This makes clear that assessment is about understanding and improving student learning, not just a hoop to jump through to address some administrative or accreditation mandate.
|Posted on January 28, 2018 at 7:25 AM||comments (0)|
A couple of years ago I did a literature review on rubrics and learned that there’s no consensus on what a rubric is. Some experts define rubrics very narrowly, as only analytic rubrics—the kind formatted as a grid, listing traits down the left side and performance levels across the top, with the boxes filled in. But others define rubrics more broadly, as written guides for evaluating student work that, at a minimum, lists the traits you’re looking for.
But what about something like the following, which I’ve seen on plenty of assignments?
70% Responds fully to the assignment (length of paper, double-spaced, typed, covers all appropriate developmental stages)
15% Grammar (including spelling, verb conjugation, structure, agreement, voice consistency, etc.)
Under the broad definition of a rubric, yes, this is a rubric. It is a written guide for evaluating student work, and it lists the three traits the faculty member is looking for.
The problem is that it isn’t a good rubric. Effective assessments including rubrics have the following traits:
Effective assessments yield information that is useful and used. Students who earn less than 70 points for responding to the assignment have no idea where they fell short. Those who earn less than 15 points on organization have no idea why. If the professor wants to help the next class do better on organization, there’s no insight here on where this class’s organization fell short and what most needs to be improved.
Effective assessments focus on important learning goals. You wouldn’t know it from the grading criteria, but this was supposed to be an assignment on critical thinking. Students focus their time and mental energies on what they’ll be graded on, so these students will focus on following directions for the assignment, not developing their critical thinking skills. Yes, following directions is an important skill, but critical thinking is even more important.
Effective assessments are clear. Students have no idea what this professor considers an excellently organized paper, what’s considered an adequately organized paper, and what’s considered a poorly organized paper.
Effective assessments are fair. Here, because there are only three broad, ill-defined traits, the faculty member can be (unintentionally) inconsistent in grading the papers. How many points are taken off for an otherwise fine paper that’s littered with typos? For one that isn’t double-spaced?
So the debate about an assessment should be not whether it is a rubric but rather how well it meets these four traits of effective assessment practices.
If you’d like to read more about rubrics and effective assessment practices, the third edition of my book Assessing Student Learning: A Common Sense Guide will be released on February 13 and can be pre-ordered now. The Kindle version is already available through Amazon.
|Posted on October 7, 2017 at 8:20 AM||comments (2)|
One of the many things I’ve learned by watching Ken Burns’ series on Vietnam is that Defense Secretary Robert MacNamara was a data geek. A former Ford Motor Company executive, he routinely asked for all kinds of data. Sounds great, but there were two (literally) fatal flaws with his approach to assessment.
First, MacNamara asked for data on virtually anything measurable, compelling staff to spend countless hours filling binders with all kinds of metrics—too much data for anyone to absorb. And I wonder what his staff could have accomplished had they not been forced to spend so much time on data collection.
And MacNamara asked for the wrong data. He wanted to track progress in winning the war, but he focused on the wrong measures: body counts, weapons captured. He apparently didn’t have a clear sense of exactly what it would mean to win this war and measure progress toward that end. I’m not a military scientist, but I’d bet that more important measures would have included the attitudes of Vietnam’s citizens and the capacity of the South Vietnamese government to deal with insurgents on its own.
There are three important lessons here for us. First, worthwhile assessment requires a clear goal. I often compare teaching to taking our students on a journey. Our learning goal is where we want them to be at the end of the learning experience (be it a course, program, degree, or co-curricular experience).
Second, worthwhile assessment measures track progress toward that destination. Are our students making adequate progress along their journey? Are they reaching the destination on time?
Third, assessment should be limited—just enough information to help us decide if students are reaching the destination on time and, if not, what we might to do help them on their journey. Assessment should never take so much time that it detracts from the far more important work of helping students learn.
|Posted on August 26, 2017 at 8:20 AM||comments (10)|
Chris Coleman recently asked the Accreditation in Southern Higher Education listserv ([email protected]) about schedules for assessing program learning outcomes. Should programs assess one or two learning outcomes each year, for example? Or should they assess everything once every three or four years? Here are my thoughts from my forthcoming third edition of Assessing Student Learning: A Common Sense Guide.
If a program isn’t already assessing its key program learning outcomes, it needs to assess them all, right away, in this academic year. All the regional accreditors have been expecting assessment for close to 20 years. By now they expect implemented processes with results, and with those results discussed and used. A schedule to start collecting data over the next few years—in essence, a plan to come into compliance—doesn’t demonstrate compliance.
Use assessments that yield information on several program learning outcomes. Capstone requirements (senior papers or projects, internships, etc.) are not only a great place to collect evidence of learning, but they’re also great learning experiences, letting students integrate and synthesize their learning.
Do some assessment every year. Assessment is part of the teaching-learning process, not an add-on chore to be done once every few years. Use course-embedded assessments rather than special add-on assessments; this way, faculty are already collecting assessment evidence every time the course is taught.
Keep in mind that the burden of assessment is not assessment per se but aggregating, analyzing, and reporting it. Again, if faculty are using course-embedded assessments, they’re already collecting evidence. Be sensitive to the extra work of aggregating, analyzing, and reporting. Do all you can to keep the burden of this extra work to a bare-bones minimum and make everyone’s jobs as easy possible.
Plan to assess all key learning outcomes within two years—three at most. You wouldn’t use a bank statement from four years ago to decide if you have enough money to buy a car today! Faculty similarly shouldn’t be using evidence of student learning from four years ago to decide if student learning today is adequate. Assessments conducted just once every several years also take more time in the long run, as chances are good that faculty won’t find or remember what they did several years earlier, and they’ll need to start from scratch. This means far more time is spent planning and designing a new assessment—in essence, reinventing the wheel. Imagine trying to balance your checking account once a year rather than every month—or your students cramming for a final rather than studying over an entire term—and you can see how difficult and frustrating infrequent assessments can be, compared to those conducted routinely.
Keep timelines and schedules flexible rather than rigid, adapted to meet evolving needs. Suppose you assess students’ writing skills and they are poor. Do you really want to wait two or three years to assess them again? Disappointing outcomes call for frequent reassessment to see if planned changes are having their desired effects. Assessments that have yielded satisfactory evidence of student learning are fine to move to a back-burner, however. Put those reassessments on a staggered schedule, conducting them only once every two or three years just to make sure student learning isn’t slipping. This frees up time to focus on more pressing matters.
|Posted on August 8, 2017 at 10:35 AM||comments (2)|
Assessing student learning in co-curricular experiences can be challenging! Here are some suggestions from the (drum roll, please!) forthcoming third edition of my book Assessing Student Learning: A Common Sense Guide, to be published by Jossey-Bass on February 4, 2018. (Pre-order your copy at www.wiley.com/WileyCDA/WileyTitle/productCd-1119426936.html)
Recognize that some programs under a student affairs, student development, or student services umbrella are not co-curricular learning experiences. Giving commuting students information on available college services, for example, is not really providing a learning experience. Neither are student intervention programs that contact students at risk for poor academic performance to connect them with available services.
Focus assessment efforts on those co-curricular experiences where significant, meaningful learning is expected. Student learning may be a very minor part of what some student affairs, student development, and student services units seek to accomplish. The registrar’s office, for example, may answer students’ questions about registration but not really offer a significant program to educate students on registration procedures. And while some college security operations view educational programs on campus safety as a major component of their mission, others do not. Focus assessment time and energy on those co-curricular experiences that are large or significant enough to make a real impact on student learning.
Make sure every co-curricular experience has a clear purpose and clear goals. An excellent co-curricular experience is designed just like any other learning experience: it has a clear purpose, with one or more clear learning goals; it is designed to help students achieve those goals; and it assesses how well students have achieved those goals.
Recognize that many co-curricular experiences focus on student success as well as student learning—and assess both. Many co-curricular experiences, including orientation programs and first-year experiences, are explicitly intended to help students succeed in college: to earn passing grades, to progress on schedule, and to graduate. So it’s important to assess both student learning and student success in order to show that the value of these programs is worth the college’s investment in them.
Recognize that it’s often hard to determine definitively the impact of one co-curricular experience on student success because there may be other mitigating factors. Students may successfully complete a first-year experience designed to prepare them to persist, for example, then leave because they’ve decided to pursue a career that doesn’t require a college degree.
Focus a co-curricular experience on an institutional learning goal such as interpersonal skills, analysis, professionalism, or problem solving.
Limit the number of learning goals of a co-curricular experience to perhaps just one or two.
State learning goals so they describe what students will be able to do after and as a result of the experience, not what they’ll do during the experience.
For voluntary co-curricular experiences, start but don’t end by tracking participation. Obviously if few students participate, impact is minimal no matter how much student learning takes place. So participation is an important measure. Set a rigorous but realistic target for participation, count the number of students who participate, and compare your count against your target.
Consider assessing student satisfaction, especially for voluntary experiences. Student dissatisfaction is an obvious sign that there’s a problem! But student satisfaction levels alone are insufficient assessments because they don’t tell us how well students have learned what we value.
Voluntary co-curricular experiences call for fun, engaging assessments. No one wants to take a test or write a paper to assess how well they’ve achieved a co-curricular experience’s learning goals. Group projects and presentations, role plays, team competitions, and Learning Assessment Techniques (Barkley & Major, 2016) can be more fun and engaging.
Assessments in co-curricular experiences need students to give them reasonably serious thought and effort. This can be a challenge when there's no grade to provide an incentive. Explain how the assessment will impact something students will find interesting and important.
Short co-curricular experiences call for short assessments. Brief, simple assessments such as minute papers, rating scales, and Learning Assessment Techniques can all yield a great deal of insight.
Attitudes and values can often only be assessed with indirect evidence such as rating scales, surveys, interviews, and focus groups. Reflective writing may be a useful, direct assessment strategy for some attitudes and values.
Co-curricular experiences often have learning goals such as teamwork that are assessed through processes rather than products. And processes are harder to assess than products. Direct observation (of a group discussion, for example), student self-reflection, peer assessments, and short quizzes are possible assessment strategies.
|Posted on June 19, 2017 at 9:30 AM||comments (1)|
Someone on the ASSESS listserv recently asked how to advise a faculty member who wanted to collect more assessment evidence before using it to try to make improvements in what he was doing in his classes. Here's my response, based on what I learned in a book I discussed in my last blog post called How to Measure Anything.
First, we think of doing assessment to help us make decisions (generally about improving teaching and learning). But think instead of doing assessment to help us make better decisions than we would make without them. Yes, faculty are always making informal decisions about changes to their teaching. Assessment should simply help them make somewhat better informed decisions.
Second, think about the risks of making the wrong decision. I'm going to assume, rightly or wrongly, that the professor is assessing student achievement of quantitative skills in a gen ed statistics course, and the results aren't great. There are five possible decision outcomes:
1. He decides to do nothing, and students in subsequent courses do just fine without any changes. (He was right; this was an off sample.)
2. He decides to do nothing, and students in subsequent courses continue to have, um, disappointing outcomes.
3. He changes things, and subsequent students do better because of his changes.
4. He changes things, but the changes don't help; despite his best effort, changes in his teaching didn't help improve the disappointing outcomes.
5. He changes things, and subsequent students do better, but not because of his changes--they're simply better prepared than this year's students.
So the risk of doing nothing is getting Outcome 2 instead of Outcome 1: Yet another class of students doesn't learn what they need to learn. The consequence is that even more students consequently run into trouble in later classes, on the job, wherever, until the eventual decision is made to make some changes.
The risk of changing things, meanwhile, is getting Outcome 4 or 5 instead of Outcome 3: He makes changes but they don't help. The consequence here is his wasted time and, possibly, wasted money, if his college invested in something like an online statistics tutoring module or gave him some released time to work on this.
The question then becomes, "Which is the worst consequence?" Normally I'd say the first consequence is the worst: continuing to pass or graduate students with inadequate learning. If so, it makes sense to go ahead with changes even without a lot of evidence. But if the second consequence involves a major investment of sizable time or resources, then it may make sense to wait for more corroborating evidence before making that major investment.
One final thought: Charles Blaich and Kathleen Wise wrote a paper for NILOA a few years ago on their research, in which they noted that our tradition of scholarly research does not include a culture of using research. Think of the research papers you've read--they generally conclude either by suggesting how some other people might use the research and/or by suggesting areas for further research. So sometimes the argument to wait and collect more data is simply a stalling tactic by people who don't want to change.
|Posted on May 30, 2017 at 12:10 AM||comments (13)|
I stumbled across a book by Douglas Hubbard titled How to Measure Anything: Finding the Value of “Intangibles in Business.” Yes, I was intrigued, so I splurged on it and devoured it.
The book should really be titled How to Measure Anything Without Killing Yourself because it focuses as much on limiting assessment as measuring it. Here are some of the great ideas I came away with:
1. We are (or should be) assessing because we want to make better decisions than what we would make without assessment results. If assessment results don’t help us make better decisions, they’re a waste of time and money.
2. Decisions are made with some level of uncertainty. Assessment results should reduce uncertainty but won’t eliminate it.
3. One way to judge the quality of assessment results is to think about how confident you are in them by pretending to make a money bet. Are you confident enough in the decision you’re making, based on assessment results, that you’d be willing to make a money bet that the decision is the right one? How much money would you be willing to bet?
4. Don’t try to assess everything. Focus on goals that you really need to assess and on assessments that may lead you to change what you’re doing. In other words, assessments that only confirm the status quo should go on a back burner. (I suggest assessing them every three years or so, just to make sure results aren’t slipping.)
5. Before starting a new assessment, ask how much you already know, how confident you are in what you know, and why you’re confident or not confident. Information you already have on hand, however imperfect, may be good enough. How much do you really need this new assessment?
6. Don’t reinvent the wheel. Almost anything you want to assess has already been assessed by others. Learn from them.
7. You have access to more assessment information than you might think. For fuzzy goals like attitudes and values, ask how you observe the presence or absence of the attitude or value in students and whether it leaves a trail of any kind.
8. If you know almost nothing, almost anything will tell you something. Don’t let anxiety about what could go wrong with assessment keep you from just starting to do some organized assessment.
9. Assessment results have both cost (in time as well as dollars) and value. Compare the two and make sure they’re in appropriate balance.
10. Aim for just enough results. You probably need less data than you think, and an adequate amount of new data is probably more accessible than you first thought. Compare the expected value of perfect assessment results (which are unattainable anyway), imperfect assessment results, and sample assessment results. Is the value of sample results good enough to give you confidence in making decisions?
11. Intangible does not mean immeasurable.
12. Attitudes and values are about human preferences and human choices. Preferences revealed through behaviors are more illuminating than preferences stated through rating scales, interviews, and the like.
13. Dashboards should be at-a-glance summaries. Just like your car’s dashboard, they should be mostly visual indicators such as graphs, not big tables that require study. Every item on the dashboard should be there with specific decisions in mind.
14. Assessment value is perishable. How quickly it perishes depends on how quickly our students, our curricula, and the needs of our students, employers, and region are changing.
15. Something we don’t ask often enough is whether a learning experience was worth the time students, faculty, and staff invested in it. Do students learn enough from a particular assignment or co-curricular experience to make it worth the time they spent on it? Do students learn enough from writing papers that take us 20 hours to grade to make our grading time worthwhile?
|Posted on March 18, 2017 at 8:25 AM||comments (11)|
My last blog post on analyzing multiple choice test results generated a good bit of feedback, mostly on the ASSESS listserv. Joan Hawthorne and a couple of other colleagues thoughtfully challenged my “50% rule”—that any questions that more than 50% of your students get wrong may suggest something wrong and should be reviewed carefully.
Joan pointed out that my 50% rule shouldn’t be used with tests that are so important that students should earn close to 100%. She’s absolutely right. Some things we teach—healthcare, safety—are so important that if students don’t learn them well, people could die. If you’re teaching and assessing must-know skills and concepts, you might want to look twice at any test items that more than 10% or 15% of students got wrong.
With other tests, how hard the test should be depends on its purpose. I was taught in grad school that the purpose of some tests is to separate the top students from the bottom—distinguish which students should earn an A, B, C, D, or F. If you want to maximize the spread of test scores, an average item difficulty of 50% is your best bet—in theory, you should get test scores ranging all the way from 0 to 100%. If you want each test item to do the best possible job discriminating between top and bottom students, again you’d want to aim for a 50% difficulty.
But in the real world I’ve never seen a good test with an overall 50% difficulty for several good reasons.
1. Difficult test questions are incredibly hard to write. Most college students want to get a good grade and will at least try to study for your test. It’s very hard to come up with a test question that assesses an important objective but that half of them will get wrong. Most difficult items I’ve seen are either on minutiae, “trick” questions on some nuanced point, or questions that are more tests of logical reasoning skill than course learning objectives. In my whole life I’ve written maybe two or three difficult multiple choice questions that I’ve been proud of: that truly focused on important learning outcomes and didn’t require a careful nuanced reading or logical reasoning skills. In my consulting work, I’ve seen no more than half a dozen difficult but effective items written by others. This experience has led me to suggest that “50% rule.”
2. Difficult tests are demoralizing to students, even if you “curve” the scores and even if they know in advance that the test will be difficult.
3. Difficult tests are rarely appropriate, because it’s rare for the sole or major purpose of a test to be to maximize the spread of scores. Many tests have dual purposes. There are certain fundamental learning objectives we want to make sure (almost) every student has learned, or they’re going to run into problems later on. Then there are some learning objectives that are more challenging—that only the A or maybe B students will achieve—and those test items will separate the A from B students and so on.
So, while I have great respect for those who disagree with me, I stand by my suggestion in my last blog post. Compare each item’s actual difficulty (the percent of students who answered incorrectly) against how difficult you wanted that item to be, and carefully evaluate any items that more than 50% of your students got wrong.
|Posted on November 21, 2016 at 2:45 PM||comments (0)|
The results of the U.S. presidential election have lessons both for American higher education and for assessment. Here are the lessons I see for meaningful assessment; I’ll tackle implications for American higher education in my next blog post.
Lesson #1: Surveys are a difficult way to collect meaningful information in the 21st century. If your assessment plan includes telephone or online surveys of students, alumni, employers, or anyone else, know going in that it’s very hard to get a meaningful, representative sample.
A generation ago (when I wrote a monograph Questionnaire Survey Research: What Works for the Association of Institutional Research), most people had land line phones with listed numbers and without caller ID or voice mail. So it was easy to find their phone number, and they usually picked up the phone when it rang. Today many people don’t have land line phones; they have cell phones with unlisted numbers and caller ID. If the number calling is unfamiliar to them, they let the call go straight to voice mail. Online surveys have similar challenges, partly because databases of e-mail addresses aren’t as readily available as phone books and partly because browsing habits affect the validity of pop-up polls such as those conducted by Survey Monkey. And all survey formats are struggling with survey fatigue (how many surveys have you been asked to complete in the last month?).
Professional pollsters have ways of adjusting for all these factors, but those strategies are difficult and expensive and often beyond our capabilities.
Lesson #2: Small sample sizes may not yield meaningful evidence. Because of Lesson #1, many of the political polls we saw were based on only a few hundred respondents. A sample of 250 has an error margin of 6% (meaning that if, for example, you find that 82% of the student work you assessed meets your standard, the true percentage is probably somewhere between 76% and 88%). A sample of 200 has an error margin of 7%. And these error margins assume that the samples of student work you’re looking at are truly representative of all student work. Bottom line: We need to look at a lot of student work, from a broad variety of classes, in order to draw meaningful conclusions.
Lesson #3: Small differences aren’t meaningful. I was struck by how many reporters and pundits talked about Clinton having, say, a 1% or 2% point lead without mentioning that the error margin made these leads too close to call. I know everyone likes to have a single number—it’s easiest to grasp—but I wish we could move to the practice of reporting ranges of likely results, preferably in graphs that show overlaps and convey visually when differences aren’t really significant. That would help audiences understand, for example, whether students’ critical thinking skills really are worse than their written communication skills, or whether their information literacy skills really are better than those of their peers.
Lesson #4: Meaningful results are in the details. Clinton won the popular vote by well over a million votes but still lost enough states to lose the Electoral College. Similarly, while students at our college may be doing well overall in terms of their analytic reasoning skills, we should be concerned if students in a particular program or cohort aren’t doing that well. Most colleges and universities are so diverse in terms of their offerings and the students they serve that I’m not sure overall institution-wide results are all that helpful; the overall results can mask a great deal of important variation.
Lesson #5: We see what we want to see. With Clinton the odds-on favorite to win the race, it was easy to see Trump’s chances of winning (anywhere from 10-30%, depending on the analysis) as insignificant, when in fact these probabilities meant he had a realistic chance of winning. Just as it was important to take a balanced view of poll results, it’s important to bring a balanced view to our assessment results. Usually our assessment results are a mixed bag, with both reasons to cheer and reasons to reflect and try to improve. We need to make sure we see—and share—both the successes and the areas for concern.
|Posted on August 18, 2016 at 12:40 AM||comments (6)|
Over the last couple of years, I’ve started to get some gentle pushback from faculty on rubrics, especially those teaching graduate students. Their concern is whether rubrics might provide too much guidance, serving as a crutch when students should be figuring out things on their own. One recent question from a faculty member expressed the issue well: “If we provide students with clear rubrics for everything, what happens when they hit the work place and can’t figure out on their own what to do and how to do it without supervisor hand-holding?”
It’s a valid point, one that ties into the lifelong learning outcome that many of us have for our students: we want to prepare them to self-evaluate and self-correct their work. I can think of two ways we can help students develop this capacity without abandoning rubrics entirely. One possibility would be to make rubrics less explicit as students progress through their program. First-year students need a clear explanation of what you consider good organization of a paper; seniors and grad students shouldn’t. The other possibility—which I like better—would be to have students develop their own rubrics, either individually or in groups, subject, of course, to the professor’s review.
In either case, it’s a good idea to encourage students to self-assess their work by completing the rubric themselves—and/or have a peer review the assignment and complete the rubric—before turning it in. This can help get students in the habit of self-appraising their work and taking responsibility for its quality before they hit the workplace.
Do you have any other thoughts or ideas about this? Let me know!
|Posted on July 9, 2016 at 7:45 AM||comments (2)|
I often describe the teaching-learning-assessment process as a four-step cycle:
1. Clear learning outcomes
2. A curriculum and pedagogies designed to provide students with enough learning opportunities to achieve those outcomes
3. Assessment of those outcomes
4. Use of assessment results to improve the other parts of the cycle: learning outcomes, curriculum, pedagogies, and assessment
I also often point out that, if faculty are struggling to figure out how to assess something, the problem is often not assessment per se but the first two steps. After all, if you have clear outcomes and you’re giving students ample opportunity to achieve them, you should be grading students on their achievement of those outcomes, and there’s your assessment evidence. So the root cause of assessment struggles is often poorly articulated learning outcomes, a poorly designed curriculum, or both.
I see this a lot in the transfer AA/AS degrees offered by community colleges. As I explained in my June 20 blog entry, these degrees, designed for transfer into a four-year college major, typically consist of 42-48 credits of general education courses plus 12-18 credits related to the major. The general education and major-related components are often what I call “Chinese menu” curricula: Choose one course from Column A, two from Column B, and so on. (Ironically, few Chinese have this kind of menu any more, but people my age remember them.)
The problem with assessing these programs is the second step of the cycle, as I explained in my June 20 blog. in many cases these aren’t really programs; they’re simply collections of courses without coherence or progressive rigor. That makes it almost impossible both to define meaningful program learning outcomes (the first step of the cycle) or assess them (the third step of the cycle).
How can you deal with this mess? Here are my suggestions.
1. Clearly define what a meaningful “program” is. As I explained in my June 20 blog entry, many community colleges are bound by state or system definitions of a “program” that aren’t meaningful. Regardless of the definition to which you may be bound, I think it makes the most sense to think of the entire AA/AS degree as the program, with the 12-18 credits beyond gen ed requirements as a concentration, specialization, track or emphasis of the program.
2. Identify learning outcomes for both the degree and the concentration, recognizing that there should often be a relation between the two. In gen ed courses, students develop important competencies such as writing, analysis, and information literacy. In their concentration, they may achieve some of those competencies at a deeper or broader level, or they may achieve additional outcomes. For example, students in social science concentrations may develop stronger information literacy and analysis skills than students in other concentrations, while students in visual arts concentrations may develop visual communication skills in addition to the competencies they learn in gen ed.
Some community colleges offer AA/AS degrees in which students complete gen ed requirements plus 12-18 credits of electives. In these cases, students should work with an advisor to identify their own,unique program/concentration learning outcomes and select courses that will help them achieve those outcomes.
3. Use the following definition of a program (or concentration) learning outcome: Every student in the program (or concentration) takes at least two courses with learning activities that help him or her achieve the program learning outcome. This calls for fairly broad rather than course-specific learning outcomes.
If you’re struggling to find outcomes that cross courses, start by looking at course syllabi for any common themes in course learning outcomes. Also think about why four-year colleges want students to take these courses. What are student learning, beyond content, that will help them succeed in upper division courses in the major? In a pre-engineering program, for example, I’d like to think that the various science and math courses students take help them graduate with stronger scientific reasoning and quantitative skills than students in non-STEM concentrations.
4. Limit the number of learning outcomes; quality is more important than quantity here. Concentrations of 12-18 credits might have just one or two.
5. Also consider limiting your course options by consolidating Chinese-menu options into more focused pathways, which we are learning improve student success and completion. I’m intrigued by what Alexandra Waugh calls “meta-majors”: focused pathways that prepare students for a cluster of four-year college majors, such as health sciences, engineering, or the humanities, rather than just one.
6. Review your curricula to make sure that every student, regardless of the courses he or she elects, will graduate with a sufficiently rigorous achievement of every program (and concentration) learning outcome. An important principle here: There should be at least one course in which students can demonstrate achievement of the program learning outcome at the level of rigor expected of an associate degree holder prepared to begin junior-level work. In many cases, an entry-level course cannot be sufficiently rigorous; your program or concentration needs at least one course that cannot be taken the first semester. If you worry that prerequisites may be a barrier to completion, consider Passaic County Community College’s approach, described in my June 20 blog.
7. Finally, you’ve got meaningful program learning outcomes and a curriculum designed to help students achieve them at an appropriate level of rigor, so you're ready to assess those outcomes. The course(s) you’ve identified in the last step are where you can assess student achievement of the outcomes. But one additional challenge faces community colleges: many students transfer before taking this “capstone” course. So also identify a program/concentration “cornerstone” course: a key course that students often take before they transfer that helps students begin to achieve one or more key program/concentration learning outcomes. Here you can assess whether students are on track to achieve the program/concentration learning outcome, though at this point they probably won’t be where you want them by the end of the sophomore year.
|Posted on April 3, 2016 at 6:50 AM||comments (2)|
Last fall I drafted a chapter, “Rubric Development,” for the forthcoming second edition of the Handbook on Measurement, Assessment, and Evaluation in Higher Education. My literature review for the chapter was an eye-opener! I’ve been joking that everything I had been saying about rubrics was wrong. Not quite, of course!
One of the many things I learned is that what rubrics assess vary according to the decisions they inform, falling on a continuum from narrow to broad uses.
Task-specific rubrics, at the narrow end, are used to assess or grade one assignment, such as an exam question. They are so specific that they apply only to that one assignment. Because their specificity may give away the correct response, they cannot be shared with students in advance.
Primary trait scoring guides or primary trait analysis are used to assess a family of tasks rather than one specific task. Primary trait analysis recognizes that the essential or primary traits or characteristics of a successful outcome such as writing vary by type of assignment. The most important writing traits of a science lab report, for example, are different from those of a persuasive essay. Primary trait scoring guides focus attention on only those traits of a particular task that are relevant to the task.
General rubrics are used with a variety of assignments. They list traits that are generic to a learning outcome and are thus independent of topic, purpose, or audience.
Developmental rubrics or meta-rubrics are used to show growth or progression over time. They are general rubrics whose performance levels cover a wide span of performance. The VALUE rubrics are examples of developmental rubrics.
The lightbulb that came on for me as I read about this continuum is that rubrics toward the middle of the continuum may be more useful than those at either end. Susan Brookhart has written powerfully about avoiding task-specific rubrics: “If the rubrics are the same each time a student does the same kind of work, the student will learn general qualities of good essay writing, problem solving, and so on… The general approach encourages students to think about building up general knowledge and skills rather than thinking about school learning in terms of getting individual assignments done.”
At the other end of the spectrum, developmental rubrics have a necessary lack of precision that can make them difficult to interpret and act upon. In particular, they’re inappropriate to assess student growth in any one course.
Overall, I’ve concluded that one institution-wide developmental rubric may not be the best way to assess student learning, even of generic skills such as writing or critical thinking. As Barbara Walvoord has noted, “You do not need institution-wide rubric scores to satisfy accreditors or to get actionable information about student writing institution-wide.” Instead of using one institution-wide developmental rubric to assess student work, I’m now advocating using that rubric as a framework from which to build a family of related analytic rubrics: some for first year work, some for senior capstones, some for disciplines or families of disciplines such as the natural sciences, engineering, and humanities. Results from all these rubrics are aggregated qualitatively rather than quantitatively, by looking for patterns across rubrics. Yes, this approach is a little messier than using just one rubric, but it’s a whole lot more meaningful.
|Posted on January 25, 2016 at 7:25 AM||comments (0)|
Of course as soon as I posted and announced my last blog on helpful assessment resources, I realized I’d omitted two enormous ones: AAC&U, which has become an amazing resource and leader on assessment in general education and the liberal arts, and the National Institute of Learning Outcomes Assessment (NILOA), which has generated and published significant scholarship that is advancing assessment practice. I’ve edited that blog to add these two resources.
Last year the folks at NILOA wrote what I consider one of eight essential assessment books: Using Evidence of Student Learning to Improve Higher Education. It’s co-authored by one of the greatest collections of assessment minds on the planet: George Kuh, Stan Ikenberry, Natasha Jankowski, Timothy Cain, Peter Ewell, Pat Hutchings, and Jillian Kenzie. They make a convincing case for rebooting our approach to assessment, moving from what they call a culture of compliance, in which we focus on doing assessment largely to satisfy accreditors, to what they call consequential assessment, the kind that truly impacts student success and institutional performance.
Here’s my favorite line from the book: “Good assessment is not about the amount of information amassed, or about the quality of any particular facts or numbers put forth. Rather, assessment within a culture of evidence is about habits of question asking, reflection, deliberation, planning, and action based on evidence” (p. 46). In other words, the most important kind of validity for student learning assessments is consequential validity.
The book presents compelling arguments for making this transformational shift, discusses challenges in making this shift and offers practical, research-informed strategies on how to overcome those challenges based on real examples of good practices. This book turned on so many light bulbs for me! As I noted in my earlier blog on eight essential assessment books, it’s a worthwhile addition to every assessment practitioner’s bookshelf.
I’ll be publishing a more thorough review of the book in an upcoming issue of the journal Assessment & Evaluation in Higher Education.
|Posted on November 2, 2015 at 6:55 AM||comments (0)|
I’ve finished a draft of my chapter, “Rubric Development,” for the forthcoming second edition of the Handbook on Measurement, Assessment, and Evaluation in Higher Education. Of course the chapter had to explain what a rubric is as well as how to develop one. My research quickly showed that there’s no agreement on what a rubric is! There are at least five formats for guides to score or evaluate student work, but there is no consensus on which of the formats should be called a rubric.
The simplest format is a checklist: a list of elements present in student work. It is used when elements are judged to be either present or not; it does not assess the frequency or quality of those items.
Then comes a rating scale: a list of traits or criteria for student work accompanied by a rating scale marking the frequency or quality of each trait. Here we start to see disagreements on vocabulary; I’ve seen rating scales called minimal rubrics, performance lists, expanded checklists, assessment lists, or relative rubrics.
Then comes the analytic rubric, which fills in the rating scale’s boxes with clear descriptions of each level of performance for each trait or criterion. Here again there’s disagreement on vocabulary; I’ve seen analytic rubrics called analytical rubrics, full rubrics or descriptive rubrics.
Then there is the holistic rubric, which describes how to make an overall judgment about the quality of work through narrative descriptions of the characteristics of work at each performance level. These are sometimes called holistic scoring guides.
Finally, there’s what I’ve called a structured observation guide: a rubric without a rating scale that lists traits with spaces for comments on each trait.
So what is a rubric? Opinions fall into three camps.
The first camp defines rubrics broadly and flexibly as guides for evaluating student work. This camp would consider all five formats to be rubrics.
The second camp defines rubrics as providing not just traits but also standards or levels of quality along a continuum. This camp would consider rating scales, analytic rubrics, and holistic rubrics to be rubrics.
The third camp defines rubrics narrowly as only those scoring guides that include traits, a continuum of performance levels, and descriptions of each trait at each performance level. This camp would consider only analytic rubrics and holistic rubrics to be rubrics.
I suspect that in another 20 years or so we’ll have a common vocabulary for assessment but, in the meanwhile, if you and your colleagues disagree on what a rubric is, take comfort in knowing that you’re not alone!
|Posted on October 16, 2015 at 7:45 AM||comments (0)|
I recently came across two ideas that struck me as simple solutions to an ongoing frustration I have with many rubrics: too often they don't make clear, in compelling terms, what constitutes minimally acceptable performance. This is a big issue, because you need to know whether or not student work is adequate before you can decide what improvements in teaching and learning are called for. And your standards need to be defensibly rigorous, or you run the risk of passing through and graduating students unprepared for whatever comes next in their lives.
My first "aha!" insight came from a LinkedIn post by Clint Schmidt. Talking about ensuring the quality of coding "bootcamps," he suggests, "set up a review board of unbiased experienced developers to review the project portfolios of bootcamp grads."
This basic idea could be applied to almost any program. Put together a panel of the people who will be dealing with your student after they pass your course, after they complete your gen ed requirements, or after they graduate. For many programs, including many in the liberal arts, this might mean workplace supervisors from the kinds of places where your graduates typically find jobs after graduation. For other programs, this might mean faculty in the bachelor's or graduate programs your students move into. The panels would not necessarily need to review full portfolios; they might review samples of senior capstone projects or observe student presentations or demonstrations.
The cool thing about this approach is that many programs are already doing this. Internship, practicum, and clinical supervisors, local artists who visit senior art exhibitions, local musicians who attend senior recitals--they are all doing a various of Schmidt's idea. The problem, however, is that often the rating scales they're asked to complete are so vaguely defined that it's unclear which rating constitutes what they consider minimally acceptable performance.And that's where my second "aha!" insight comes into play. It's from a ten-year-old rubric developed by Andi Curcio to assess a civil complaint assignment in a law school class. (Go to lawteaching.org/teaching/assessment/rubrics/, then scroll down to Civil Complaint: Rubric (Curcio) to download the PDF.) Her rubric has three columns with typical labels (Exemplary, Competent, Developing), but each label goes further.
- "Exemplary" is "advanced work at this time in the course - on a job the work would need very little revision for a supervising attorney to use."
- "Competent" is "proficient work at this time in the course - on a job the work would need to be revised with input from supervising attorney."
- And "Developing" is "work needs additional content or skills to be competent - on a job, the work would not be helpful and the supervising attorney would need to start over."
Andi's simple column labels make two things clear: what is considered adequate work at this point in the program, and how student performance measures up to what employers will eventually be looking for.
If we can craft rubrics that define clearly the minimal level that students need to reach to succeed in their next course, their next degree, their next job, or whatever else happens next in their lives, and bring in the people who actually work with our students at those points to help assess student work, we will go a long way toward making assessment even more meaningful and useful.
|Posted on September 15, 2015 at 7:10 AM||comments (0)|
On September 24, I’ll be speaking at the CoursEval User Conference on “Using Student Evaluations to Improve What We Do,” sharing five principles for making student evaluations of teaching useful in improving teaching and learning:
1. Ask the right questions: ones that ask about specific behaviors that we know through research help students learn. Ask, for example, how much tests and assignments focus on important learning outcomes, how well students understand the characteristics of excellent work, how well organized their learning experiences are, how much of their classwork is hands-on, and whether they receive frequent, prompt, and concrete feedback on their work.
2. Use student evaluations before the course’s halfway point. This lets the faculty member make mid-course corrections.
3. Use student evaluations ethically and appropriately. This includes using multiple sources of information on teaching effectiveness (teaching portfolios, actual student learning results, etc.) and addressing only truly meaningful shortcomings.
4. Provide mentoring. Just giving a faculty member a summary of student evaluations isn’t enough; faculty need opportunities to work with colleagues and experts to come up with fresh approaches to their teaching. This calls for an investment in professional development.
5. Provide supportive, not punitive, policies and practices. Define a great teacher as one who is always improving. Define teaching excellence not as student evaluations but what faculty do with them. Offer incentives and rewards for faculty to experiment with new teaching approaches and allow them temporary freedom to fail.
My favorite resource on evaluating teaching is the IDEA center in Kansas. It has a wonderful library of short, readable research papers on teaching effectiveness. A particularly helpful paper (that includes the principles I’ve presented here) is IDEA Paper No. 50: Student Ratings of Teaching: A Summary of Research and Literature.