Coefficient Cronbach’s α is the most widely used for estimating reliability. Researchers have
used the index extensively in the papers that need to report its reliability, but many scholars have also
questioned it. The α coefficient is used as reliability and must satisfy the “essential tau-equivalence”
assumption. This assumption is too strict and difficult to meet, and its violation may lead to α
overestimating or underestimating the reliability. Using Cronbach’s α to estimate internal consistency is
inappropriate. The acceptable lower bound to the reliability of a test is often set empirically, and there is
no precise standard. Researchers increase the α value by deleting items, which may also lead to a decrease
in the actual reliability of the scale. Although these problems exist, α has been widely used in related
research for a long time. This is due to the following reasons: many research fields involve reporting
reliability coefficients, researchers have not been taught how to use α correctly for a long time; in addition,
standard statistical software has the function of calculating α, which is convenient for calculation; the
editors also have requirements for reporting α in the paper. McDonald pointed out that α is a particular
case of MacDonald’s ω, and ω becomes α when the “essential tau-equivalence” is satisfied. ω is better
than α when the “essential tau-equivalence” cannot be satisfied in reliability estimation. However, the
calculation of ω must use confirmatory factor analysis (CFA), which is challenging to implement in the
pre-computer era. Researchers have gradually started to use ω instead of α in their research, and more and
more people have accepted ω. However, whether MacDonald’s ω should be used instead of Cronbach’s
α, there is still a heated debate in the academic community. Opinions on ω mainly focus on the fact that
the actual values of ω and α are not significantly different in the calculation. That ω may show more
estimation failures when the sample size and overall reliability are small. It is unreasonable to abandon α
or be unwilling to move forward and stick to α. In future research, use McDonald’s omega and Cronbach’s
alpha for reliability estimation to coexist for a long time and complement each other.