A Study of the Effectiveness of Web-Based Homework in Teaching Undergraduate Business Statistics

Web-based homework (WBH) Technology can simplify the creation and grading of assignments as well as provide a feasible platform for assessment testing, but its effect on student learning in business statistics is unknown. This is particularly true of the latest software development of Web-based tutoring agents that dynamically evaluate individual students' skill level and purport to respond with appropriate, targeted teaching to improve learning efficiency. In this article, we compare traditional, textbook-based homework assignments with three systems of WBH for undergraduate business statistics courses: ALEKS, PH Grade Assist, and custom-made online quizzes in Blackboard. These systems represent a range of media from artificial intelligence–based tutoring to instructor-controlled objective testing. Using a common assessment test, we compare the performance of students taught with these different systems. Our study finds, as we anticipated, that student performance depends significantly upon teacher experience and student academic competence. Once these factors are controlled for, however, the technique used to deliver homework makes little difference in student success. In contrast to other published research, we do not find any advantage to automated tutoring and identify some limitations of this approach based on both instructor and student feedback.