January 4, 2021
Teachers and administrators are grappling with the obstacles associated with testing students in a non-supervised environment. They are accustomed to a classroom setting in which privacy folders are up, phones/devices are stored away, and there is no talking or leaving the room. However, in a virtual setting, teachers lose control of all of that.
Now, they must consider students who may continue to use the internet to find answers, ask a friend or sibling to do the work with them, or even just copy/paste the assignment that someone else has posted online. Ensuring the validity of test results and the honesty of students completing the work is critical in maintaining the integrity of the coursework and the outcomes of the students.
The Potential Solution
Rather than view the online testing environment as flawed or compromised, teachers ought to consider the benefits of accessing technology during evaluations. For example, projects and papers are starting to replace multiple-choice tests due to the increased degree of difficulty when it comes to attempting to cheat on a paper or project.
AI advancements have developed tools including plagiarism verification to ensure student writing is representative of their original ideas. AI also includes tools for students from bibliographic supports to visually appealing content creation and even coding platforms that students can use to demonstrate learning in creative and unique ways.
The testing environment no longer requires silence and no. 2 pencils, rather, it requires access to technology, a drive to explore learning, and a willingness to offer non-traditional modes of demonstration.
Finally, even if teachers insist upon multiple-choice tests, AI can save time by grading the tests quicker and pointing out trends and anomalies among student responses (e.g., student A and B submitted 100% of the same answers, Student C spent an average of 2.27 minutes on each question, or 92% of students missed question 4). Maximizing the use of AI can help teachers gather data to understand how students learn, which concepts may need reteaching, or perhaps which students may have cheated.
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