The Dynamics of Inferential Interpretation in Experiential Learning: Deciphering Hidden Goals from Ambiguous Experience

Abstract

According to the Carnegie School tradition of experiential learning, learning processes are driven by interpretations of experience relative to an observable goal. While prior research has considered how ambiguity may complicate interpretation, it has seldom considered how ambiguous experience emanating from the enactment of hidden goals may complicate the interpretive process. Drawing on a 13-month inductive study of CryptoTradingGroup (CTG), a distributed financial organization, and its interactions with MajorCryptoCommunity (MCC), a cryptocurrency investment community, we examine how actors engage in effective interpretation and learning when they face hidden goals and ambiguous experience. We examine how perpetrators in CTG plotted a hidden market manipulation goal in a backstage secret chatroom while simultaneously targeting MCC with invalid information enacted in the frontstage. Our analysis unpacks the dynamics of how MCC deciphered the hidden market manipulation goal and stopped the fraud through a process that we label inferential interpretation. In shifting away from a model of effective learning with statistical inference, in which interpretation is rarely examined, inferential interpretation shows how heterogeneous actors construct understandings from cues embedded in ambiguous experience during the learning process. Our study makes interpretation, i.e., the construction of meaning, central to conceptions of experiential learning when reality, causality, and intentionality are obscured.