AN AUTOMATED TOOL FOR INDIVIDUALIZED GUIDANCE IN A LARGE-SCALE COURSE

摘要

Online courses have been proposed and debated among universities, numerous college administrators, faculty, and students. On one hand, online education can reduce overhead while enrolling more students. Administration wants to enroll more students while incurring minimal overhead costs. However, simply translating the classroom lectures and materials to an online environment does not necessarily produce equivalent student performance and satisfaction from the course compared to an in-class environment. Since there is no standard in online education, it has produced erratic results in terms of student performance and costs to students as well as administration. A change in teaching and learning methodology by both teachers and students is required to take the most advantage from today's technology and apply it toward improving student performance and participation. This article overviews plans to research and create an automated learning tool to provide an individualized learning experience for students in large hybrid or online university courses while keeping overall costs and time commitment down as well as improve overall student performance. This way, we get a 1-to-1 experience where the tool studies student weaknesses, reviews their progress, and provides initial guidance without the need for direct intervention from instructors or teaching assistants. A new methodology and system will be introduced to simulate the basic day-to-day interaction a student may have with an instructor. Software algorithms and interdisciplinary concepts will be pioneered in increasing the effectiveness of existing teaching and learning methodologies by utilizing an automated tool to proactively assess students' abilities and individually refer them to other examples or modules where they can find additional help.