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Test anxiety: we’ve all experienced it. Your palms get sweaty. Your stomach churns. You pen up the paper exam and suddenly your mind goes blank. You panic and, unless you manage to calm yourself and refocus quickly, your test results end up having no real connection to your level of ability or knowledge.
This is the experience that most every student faces at one point or another in their academic careers. It’s also an experience with which every educator is all too familiar, as they watch their most talented and promising students crash and burn in the face of anxiety.
There is hope on the horizon, however, and it’s coming from a somewhat unlikely source: artificial intelligence (AI). In fact, the increasing incorporation of AI in the classroom is promising to revolutionize standardized testing, helping students and teachers alike in real-time.
Education and Technology: A Long History
Technology has been aiding students and educators alike for centuries. From the invention of the pencil in the 18th century to the advent of the internet in the 20th, processes of teaching and learning have been greatly enhanced by technological innovation.
In contemporary classrooms, ed tech such as electronic whiteboards and handheld digital devices are providing educators with an unprecedented capacity to optimize students’ learning experience. AI technologies, in particular, are proving extremely effective in enabling individualized instruction.
Indeed, the unique and extraordinary potential for AI to personalize learning may well instigate the next great transformation in education, particularly when it comes to student assessment and standardized testing.
The Agony and the Ecstasy of Assessment
As challenging as student assessments may be, they’re also essential to education. Not only are assessments necessary to gauge students’ progress and to evaluate their content mastery, but they’re also key to defining the students’ individual learning needs.
The problem, however, is that student assessment has for far too long been based on a one-size-fits-all approach that excludes or marginalizes many students. Historically, such deficiencies were rooted in technological limitations, including the lack of a viable alternative to pencil and paper-based assessments.
For students with special needs, including those with mobility or sensory impairments or neurological differences, typical instruction methods and standardized testing formats were largely inaccessible. Thus, these students were often left without the opportunity to demonstrate their knowledge, aptitudes, and needs. Consequently, educators were unable to formulate an effective approach for accommodating students’ learning needs and differences.
Assistive technologies, including AI-based devices, can facilitate assessment both for “typical” students and for those with special learning needs. For example, neurodivergent students who may have attentional deficits can sit down for a digital assessment using AI-enabled software and, within a matter of minutes, the technology can evaluate the student’s subject matter proficiency with an extremely high level of accuracy using machine learning.
This means that students with conditions such as attention deficit hyperactivity disorder (ADHD) do not have to slog through a 200-question paper test for educators to understand their particular skills, strengths, and weaknesses.
AI and Formative Assessment
The use of AI in student testing isn’t just profoundly beneficial for students with special needs. As previously suggested, all learners can benefit from AI-based testing. Specifically, digital tests are highly responsive, adapting in real-time to the student’s engagement with the technology.
AI-based testing, for example, can immediately adjust the difficulty level of questions based on the student’s performance to previous ones. In addition, students typically receive immediate results and feedback on machine-based assessments, allowing them to get a clear snapshot in real time of their particular strengths, as well as the areas on which they need more work.
Ultimately, the transition from paper assessments to AI-based testing signifies a transition from cumulative to formative testing. Instead of the high-stakes, one-shot-only assessment at the “end” of the learning unit or academic year, the student is continuously assessed using platforms that are often more familiar to and engaging for the student.
These brief, frequent, and responsive assessments allow for a truer evaluation of the student’s current needs, which in turn enables both the human educator and the machine-based assessment to modify the learning content to the student’s individual needs. On-going, formative assessments enhance students’ progression because AI-driven testing can instantaneously adapt content to levels that are equal to or slightly above the student’s level of proficiency, supporting content mastery through a sort of breadcrumb approach. This is a strategy that paper-based assessments simply can’t accommodate.
In addition, AI-based testing provides for a less traumatic and more engaging experience. Digital assessments, for instance, can be completed anywhere and at any time, including from the comfort of the student’s home. Something as simple as avoiding the long commute or the sterile testing environment can help students relax, learn more, and perform better. Similarly, machine-based testing can also assess students’ proficiency through the use of gamification, requiring students to solve puzzles using math, science, and reading on platforms highly similar to the gaming platforms students are likely to be familiar with and confident in.
Education and technology have long been close allies. However, the introduction of artificial intelligence (AI) systems in student assessment may well revolutionize education for students and teachers alike.
Go to Publisher: Emerging Education Technologies
Author: Luke Smith