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When Zoey Solano was in high school, she resisted the idea of going into the “family business” of elementary education. “Everyone expected me to be a teacher, and I told myself I wasn’t going to do that,” she says. But when I thought about it, I couldn’t see myself doing anything else.”
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Gateway courses, the first credit-bearing classes students take on the path to their major or degree, should provide foundational knowledge and skills that students need to succeed. However, some faculty and institutions have an unfortunate tendency to treat them as “weed-out” courses to screen students they deem not “college ready.” As a result, gateway courses have high DFW rates that disproportionately impact minoritized, low-income, and first-generation students.
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Selecting and implementing courseware is challenging for faculty, campus leaders, instructional designers, and IT professionals, and it requires attention from all parts of an institution. Looking at successful adaptive courseware implementations can be a useful way to address and anticipate some of those challenges.
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As a Learning Designer with the Dutton Institute for Teaching and Learning Excellence at Pennsylvania State University, Megan Kohler believes her work is similar in a key way to her earlier career as a professional actor—both are about connecting with audiences.
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Courseware offers potential benefits such as flexibility and convenience, support for remote and hybrid learning, and cost savings. But one challenge for faculty selecting courseware is that the terms “adaptive learning” and “adaptive courseware” are often used in ways that are confusing or misleading.
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While most colleges and universities have IT professionals dedicated to cybersecurity issues, everyone in the institution has a role to play. This is especially true of faculty who are involved in selecting new courseware products, using them alongside other technology, asking large numbers of students to use multiple technology products, collecting data about students, and may have research projects involving sensitive data.
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