P670: Comparison of two online homework systems based on student performance within the context of the Technology Acceptance Model in Introductory Chemistry

Author: Anna Bayless George, University of Wisconsin -La Crosse, USA

Co-Author: Benjamin George, University of North Texas, USA

Date: 8/6/14

Time: 9:55 AM10:15 AM

Room: LTT 103

Related Symposium: S13

Several investigations regarding the use of online homework have been conducted to evaluate their effectiveness and value in university science courses. These studies tend to evaluate either student perceptions or student performance. Davis (1985) developed the Technology Acceptance Model (TAM) to understand the user acceptance process of computer and information systems as well as to provide a theoretical basis for empirically measuring user acceptance. The relationship between student perceptions regarding online homework, as opposed to written homework, and student performance in an introductory chemistry class was analyzed within the context of this model. Students enrolled in a section of chemistry for non-science majors were assigned homework previously given out of the back of the book, using the online homework program that accompanies the textbook. A separate sample of students enrolled in chemistry for non-science majors used a commercially available online homework program that was independent from the textbook. Student perceptions and chemistry content knowledge were collected of both separate samples at the beginning of the semester and again at the end of the semester to evaluate changes in perception and content knowledge. This population is a representative sample of students at the beginning of their academic careers in the Midwest who are considered to be part of the “Digital Native” generation. The data collected from these two samples was used to compare the relationship between student perceptions and student performance in introductory chemistry for two online homework programs. Post hoc analysis was performed to isolate potential significant differences between the two samples.