Utilizing Instructional Consultations to Enhance the Teaching Performance of Engineering Faculty

Although many kinds of data can be used to guide instructional consultations, research comparing the efficacy of such data is scant, especially in engineering. In this study, multiple modes of assessment were used to evaluate the impact of consultations informed by different kinds of data. This study illuminates two key aspects of instructional consultations: (1) their efficacy varies depending on the kind of data used to guide them, with student feedback from a Small Group Instructional Diagnosis (SGID) having the largest positive impact, and (2) the instructional consultant plays a key role in helping both interpret the available data and identify strategies for improvement. These findings suggest three implications for practice: (1) whenever possible, SGID‐based consultations should be offered systematically and proactively for engineering faculty, (2) data for other kinds of consultations should be tailored to the needs of the individual instructor, and (3) instructional consultants should be available to collaborate with faculty to enhance their teaching, thereby building an engineering culture that actively supports teaching and learning.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94604/1/j.2168-9830.2008.tb00989.x.pd

Norming of Student Evaluations of Instruction: Impact of Non-Instructional Factors

Student Evaluations of Instruction (SEIs) from about 6000 sections over four years representing over 100,000 students at the college of business at a large public university are analyzed, to study the impact of non-instructional factors on student ratings. Administrative factors like semester, time of day, location, and instructor attributes like gender and rank are studied. The combined impact of all the non-instructional factors studied is statistically significant. Our study has practical implications for administrators who use SEIs to evaluate faculty performance. SEI scores reflect some inherent biases due to non-instructional factors. Appropriate norming procedures can compensate for such biases, ensuring fair evaluations

New directions for teaching and learning

Publ. comme no 31, fall 1987 de la revue New directions for teaching and learningBibliogr. à la fin des textesIndex: p. 93-9