Open AccessTeaching Methods And Technologies: Aggregated Faculty Analysis, Conclusions And Recommendations Phase IV
Author(s) -
Dennis L. Payette,
Daniel A. Verreault
Publication year - 2007
Publication title -
journal of college teaching and learning/journal of college teaching and learning
Language(s) - English
Resource type - Journals
eISSN - 2157-894X
pISSN - 1544-0389
DOI - 10.19030/tlc.v4i6.1574
Subject(s) - variety (cybernetics) , set (abstract data type) , adjunct , value (mathematics) , aggregate (composite) , data collection , medical education , psychology , computer science , mathematics education , sociology , medicine , social science , philosophy , linguistics , materials science , artificial intelligence , machine learning , composite material , programming language
This paper culminates three years of research on the use of various teaching technologies and methods by the faculty of Adelphi University School of Business in Garden City, New York. Previously, papers on this research were published on the development of the research instrument, the administration and data analysis for full time faculty (Part II), and most recently the analysis of data from adjunct faculty (Part III). This paper (Part IV) includes a number of new faculty additions to the data set and analyzes and interprets the aggregated data. Our overall findings suggest a wide variety of soft and hard technologies where the aggregate group expressed a statistically significant higher perceived “value of use” than a “level of use”. Newer classroom types were also valued more highly than used. The research controlled for “department”, “status”, and “teaching experience”. Factors tended to be non-significant with some interesting exceptions. We note our conclusions, make policy recommendations, and suggest opportunities for expanded research.