Tag: faculty

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The Assessment Crisis is Bigger than AI

The last few months have seen my campus scrambling to get back to in-person assessment and to reopen testing centers. Like many universities that quietly had deemphasized such exams during the COVID years, now at UC Irvine there is rising faculty demand to quickly change course. Many worry about the validity of take-home and online assessments, as campus officials search for rooms or even build new ones. Meanwhile, already stressed students feel increasingly desperate over high-stakes tests that can make or break academic success. While the crisis seems recent at UCI, what’s really happening predates the rise of generative AI and won’t be fixed with more exam rooms.

Much of higher education now sees online assessment as an arms race it can’t win, with over 150 institutions planning to end it this year. Earlier this month, the Law School Admission Council (LSAC) announced t it would return the LSAT to in-person testing by summer 2026, citing “security concerns,” “score inflation,” and “the misuse of technology to facilitate cheating.”[1]  All Ivy League schools also are reverting to standardized tests for admissions after eliminating them during the last decade.  Complicating matters further is the reality of cash-strapped schools facing infrastructure bottlenecks because they’ve  repurposed or sold off testing centers.[2]  Driving this frantic backtracking is the logical but incorrect belief that assessment is losing meaning at a time when ChatGPT can generate answers in a few seconds. Hence the current retreat to blue books, testing rooms, and internet-free conditions.

“Generative AI did not create assessment issues. It revealed them,” according to Emma Ransome of Birmingham City University.[3]  Ransome explains that traditional measures like timed exams, standardized tasks, and recall-based tests historically have done poorly in evaluating skills universities claim to instill such as critical thinking, ethical judgement, and synthesizing ideas. Generative AI has made the disconnect between what is being measured and what is being taught even more apparent. If a large language model can successfully complete a multiple choice pharmacology exam, or if an LLM can generate a decent survey essay about the causes of World War I, one shouldn’t be asking how to stop students from using it.  Instead the issue should be what kind of knowledge those conventional measures assessed in the first place.

Continue reading “The Assessment Crisis is Bigger than AI”

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The Problem with Rigor

“It’s Time to Cancel the Word Rigor,” read a recent headline in education press.[1]  The article detailed growing concerns about hidden bias within what many see as conventional teaching practices. Here, “rigor” was taken to task for throwing roadblocks up for some students more than others, even as its exact meaning remains vague. Webster’s Dictionary defines rigor as “severity, strictness or austerity,” which educators often translate into difficult courses and large amounts of work, rationalized in the interest of excellence and high standards.[2]

While there is nothing wrong with challenging coursework, per se, this interpretation of rigor often becomes a recipe for failure for otherwise intelligent and hardworking students.  Such failures can result when rigor is used to incentivize or stratify students, as in gateway or “weed out” courses with prescribed grading targets, or situations where faculty overuse tests as motivation. Rigor discussions I have witnessed rarely consider instructional quality, teaching effectiveness, or principles of learning. Instead faculty complain about poor student attention, comprehension, or commitment. As the Chronicle explains, “all credit or blame falls on individual students, when often it is the academic system that creates the constructs, and it’s the system we should be questioning when it erects barriers for students to surmount or make them feel that they don’t belong.”[3] Continue reading “The Problem with Rigor”

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Why Professors Ignore the Science of Teaching

A recent article appearing in the Chronicle of Higher Education explored the apparent reluctance of college and university professors to embrace the growing body of research about how students learn and what teaching methods work best. While many faculty simply cling to what has worked for them in the past, others feel overworked and unable the consider changing. In the meantime, an increasingly diverse student population experiences increasing inequity as a result.

Beth McMurtrie’s “Why the Science of Teaching is Often Ignored” opens with a discussion of a recent study by five Harvard University researchers who published some novel research. The group was trying to figure out why active learning, a form of teaching that has had measurable success, often dies a slow death in the classroom. They compared the effects of a traditional lecture with active learning, where students solve problems in small groups.

The results were not surprising; students who were taught in an active method performed better on standardized tests. The academic press praised the study for its clever design and its resonance with professors who had trouble with active learning. Yet despite being praised in some quarters, the study was criticized in others.

This mixed reaction reveals a central paradox of higher education, according to McMurtrie. Teaching and learning research has grown dramatically over the decades, encompassing thousands of experiments, journals, books, and programs to bring learning science  into classrooms. But a lot of faculty members haven’t read it, aren’t sure what to do with it, or are skeptical. Continue reading “Why Professors Ignore the Science of Teaching”