Elsevier Adaptive Quizzing for Imaging Sciences, 2nd Edition
Elsevier Adaptive Quizzing - Next Generation
Elsevier Adaptive Quizzing (EAQ) for Imaging Sciences, 2nd Edition integrates seamlessly into your course to help students of all skill levels focus their study time and effectively prepare for summative exams and, ultimately, their licensure exam. EAQ is comprised of a bank of high-quality practice questions that allows students to advance at their own pace — based on their performance — through multiple mastery levels for each topic. A comprehensive dashboard allows students to view their progress and stay motivated. The educator dashboard and reporting capabilities enable you to monitor the activity of individual students, assess overall class performance, and identify areas of strength and weakness, ultimately helping to achieve improved learning outcomes and licensure exam pass rates.
- UNIQUE! Elsevier’s trusted, market-leading content serves as the foundation for all questions, which are written, reviewed, and leveled by experienced educators, item writers, and authors.
- Confidence level indicators allow you to indicate your confidence when submitting answers, providing valuable insight into areas where you might be overconfident and require further study.
- UNIQUE! Practice in Study Mode, which provides immediate feedback, or in Exam Mode where the quiz is timed and results are summarized at the end.
- UNIQUE! In addition to detailed rationales for each question, select questions include interactive, multimedia resources such as illustrations, animations, videos, audio clips, summary tables, and study tips to help you master challenging material.
- Engaging, easy-to-use interface ensures that you can navigate through the program with ease.
- Multiple mastery levels for each topic allow you to progress from one level to the next based on your performance.
- A comprehensive dashboard allows you to view your personal learning progress with summaries of your strengths, weaknesses, mastery levels, and normative data.
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