Student Evaluation of Teaching

This is an interesting study about Student Evaluation of Teaching . I am posting this study just in case you would like to contribute insight(s).

Student evaluations of teaching are not only unreliable, they are significantly biased against female instructors.

A series of studies across countries and disciplines in higher education confirm that student evaluations of teaching (SET) are significantly correlated with instructor gender, with students regularly rating female instructors lower than male peers. Anne Boring, Kellie Ottoboni and Philip B. Stark argue the findings warrant serious attention in light of increasing pressure on universities to measure teaching effectiveness. Given the unreliability of the metric and the harmful impact these evaluations can have, universities should think carefully on the role of such evaluations in decision-making.. read more …

Student evaluations of teaching are not only unreliable, they are significantly biased against female instructors.



Manila Research Exchange 55


Dear Fellow Researchers,

Welcome to Manila Research Exchange 55! This website is intended as a forum for the sharing of ideas and collaboration of research work(s). Beginners in research can get help from conceptualization to data analysis. We can connect you with people who are interested in your work either from the academe or industry including conferences.

Feel free to join us.

Very truly yours,

Hector John T. Manaligod, PhD






Starting with Normal Curve

My fascination  with statistics started in the late 7os when i was a young student of Psychology. I was working with a government computer agency as computer operator then and many time to spare to read during my break. One day, a beautiful office mate asked me a favor if i can solve her statistics assignment which  i readily accepted given her irresistible charm. She requested me to teach her about the concept of normal curve distribution and standard score (z-score). There i begun to understand that  a normal curve is divided into 2 parts —  50% below the mean and 50% above the mean. Simple. Each half is divided into 4 parts of .13%, 2.14%, 13.59%, and 34.13% which would total 49.99 or 50%. The center being the average or what we call the mean. One standard deviation + or –  the mean would be 68.26 (that is  34.13% + 34.13%). Two standard deviations above and below the mean would equal to 95.44% (i.e., 13.59 + 34.16+34.16 + 13.59). Three standard deviations below and above the mean would be 99.72%. The values represented by percentage are your probability values given a normal distribution. To get a clearer understanding of what i am saying, please look at the figure below.

Normal_curve_probability    My next blog will be about the concept of descriptive statistics and dispersion. Hasta luego!