Abstract
This article contributes to the larger literature on meaning construction and misunderstanding by developing a typology of listening habits and a corresponding scale to measure individual differences in typical ways of listening. Our typology includes four habits of listening grounded in two underlying aspects of meaning, content and relational, found in any spoken message. Analytical Listening (AL) involves filtering information through an interest in results and facts, while Conceptual Listening (CL) involves filtering information through an interest in concepts and possibilities. Connective Listening (CV) involves filtering information through interests in others (people, groups, processes, or audiences), while Reflective Listening (RV) involves filtering information through one’s own interests and purposes. Results from two studies provide construct, convergent, and discriminant validity evidence for the resulting ECHO Listening Profile. In particular, exploratory and confirmatory factor analyses were used to create a 40-item version of the ECHO Listening Profile (ECHO) that was shown to map onto a conceptually similar measure of listening habits, the Listening Style Profile; ECHO did not, however, fully duplicate that scale and thus adds to our knowledge of how all listening is biased. Moreover, through use of comparative forced-choice scaling, ECHO reduces concerns found with self-reporting of listening, including response bias. Future work investigating the impact of Connective, Reflective, Analytical, and Conceptual Listening on how people navigate their personal and professional lives is warranted.
Notes
1 As in the example provided on page 4, A = Connective, B = Reflective, C = Analytical, and D = Conceptual.
2 For Bayesian MAP scores, which are regressed-to-median estimates of latent traits, the formula is:
3 For CV, unexpected loadings include (a) items written to measure other traits but loading on CV; for example, item “I’m most often misperceived as … insensitive to others’ needs” (block 25, option B) written to indicate Reflective Listening (RV) actually indicates the low end of CL; or (b) items written to measure CL but loading on other traits, for example item “If a co-worker cuts me off or talks over me …. I will tend to feel disrespected or slightly hurt, even if I don‘t show it” (block 38, option A) written for CL but actually indicating RV (which may not be surprising with the focus on self rather than others in this statement). For CL, unexpected loadings included (a) items written to measure other traits but loading on CL; for example, item “If I need to make a quick decision I’ll … usually make it based on what I’ve experienced to work in the past” (block 35, option B) written for RV but indicating CL; or (b) items written to measure CL but loading on other traits; for example item “When bored or uncomfortable in a meeting run by a superior, I’m most likely to … fidget and start thinking about other things (block 12, option D) written for CL but actually indicating AL.
4 Examples include: “People think of me as…. a deep listener” (block 7 option B), which appears to be a better measure of Analytical than Reflective Listening; and “People come to me when …. they can benefit from my area of expertise” (block 8 option B), which emphasizes others benefitting, not the subject benefitting as the Reflective style definition would suggest. In addition, some items designed to measure RV actually appear to indicate Analytical Listening (AL). For example, block 5 option B “When someone says something I perceive as inaccurate, I‘m most likely to…. stop them and ask for clarification”, which is designed to indicate RV, appears to fit better with AL.
5 For example, in block 31, “When someone is speaking to me and I‘m pressed for time, I‘m most likely to think…”, both option B “..This person is impinging on my time” and option C “…. Could this person please get to the point?” are very similar in meaning and do not differentiate well between the two styles.
6 For example, block 27 designed to indicate low ends of all traits, failed to produce any salient loadings. Other blocks, such as 22 or 23, produced loadings on only one factor out of four. These blocks provide very little information on the measured traits, and instead introduce noise in the model.