Engineering, teaching, and technology: A nationwide assessment of instructional internet use by engineering faculty.

摘要

There has been an explosion of internet use among college students over the last decade for at least two important reasons: the proliferation of available resources and the arrival of a digital native generation to university campuses. Not surprisingly, engineering students are entering undergraduate programs possessing a much different skill set than previous generations, which has led to a decline in the popularity of traditional engineering pedagogy. Numerous conceptual models have been developed in the field of instructional technology, as researchers have attempted to classify and effectively integrate new technology practices into 21st century educational contexts. One of the most prominent models is Technology, Pedagogy and Content Knowledge (TPACK), which separates instructors' knowledge into the three listed categories and describes their instructional strategies based on the presence and level of integration of the three knowledge categories. A newer, engineering-specific model separates engineering faculty into three archetypes based on their instructional internet use: internet adopters, internet users, and internet resisters.;This study quantitatively assesses the instructional internet use by a sample of 1126 tenured and tenure-track engineering faculty in the United States. Factor analysis revealed three significant factors: use of internet resources for content delivery, guiding students' internet research, and faculty beliefs on the usefulness of internet resources. The distribution of these factors was used to attempt to identify each of the three archetypes, and to discretely measure the presence and level of integration of the technology component of the TPACK model. While exceptional cases could be identified as internet adopters or resisters, the results do not support the existence of three unique archetypes. Similarly, the presence and degree of technology integration does not fit any categorical model, but rather a broad spectrum of internet technology usage and beliefs. Finally, regression analyses show that demographic and institutional variables are only minimally predictive of faculty beliefs and practices regarding instructional internet use.;This study contributes to the understanding of instructional internet use in undergraduate engineering education, and provides insight into the applicability of two instructional technology models. Findings from the study may also inform institutional policy and practice regarding professional development initiatives.