Are There Typological Characteristics of Individual Unlearning?

Organizations have sought solutions to produce consistent, competent practices while updating organizational processes. A traditional method of learning used strategies of identifying gaps in knowledge, and teaching lacking information to close gaps. Faulty learning completion processes often yield decreased work product quality, and productivity, or increased product costs. Knowledge base change creates ongoing difficulties for individuals who must unlearn, store, and use new knowledge processes to update the old. Knowledge change, or unlearning, speculated to involve a replacement of prior knowledge remains unconceptualized due to limited, anecdotally based research. This qualitative study aims to further characterize unlearning initiation processes, and clarify knowledge replacement factors: 1) How does individual unlearning initiate? and, 2) What factors contribute to the unlearning process? Three weekly-spaced interviews with 31 participants categorized unlearning using Rushmer and Davies’ (2004) typological unlearning model. Predominately two knowledge change typologies were demonstrated and a new unlearning model developed

Unlearning in crisis: Forces of change in unlearning

The study of unlearning continues to be important, not only due to the relevance of the concept itself, but in light of current strong, unforeseen forces, knowledge change opportunities have been created beyond our prediction. A knowledge exchange is often needed to revise processes, use new technologies, or due to forces that stem from catastrophic situations. Examples include economic, such as in business failures or the recent public health concerns from the COVID-19 pandemic. Building from new insights using the typological model from Rushmer and Davies (2004), deep unlearning may the end result of catastrophic forces of change. First, deep unlearning occurs with striking events, or yield change that adds anxiety, psychological, or technological upset. Second, inherent in many catastrophic changes are rapid interruptions in the trajectory of “previous” actions and unique processes toward recovery where knowledge base may be forever altered. We address the following question: “Is Rushmer and Davies’ deep unlearning typology exhibited during catastrophic situations?” This theoretical paper examines the concept of deep unlearning, the process of replacement or lack of use of a belief, action, or process in a context of an emergency situation where little is currently known. What type of agent for change would be needed? Will unintended consequences not be identified by individuals and organizations; what may be the cost to future learning skills when deep unlearning of current tasks occurs? Third, some insights and directions for future research are presented

Introduction to Organizational Learning Minitrack

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Perceptions of Successful Unlearning in Hearing Aid Practioners

In patient care, maintaining skill competencies during technological advances requires effective knowledge changes processes. One method used consists of task repetition until errors are non-existent and successful demonstration of new learning is complete however, adjusting to numerous procedural changes may be difficult. Determining how to maximize change process during competency acquisition is essential. The strategy of how to change or “unlearn” previous actions and acquire new competencies successfully has been of interest. Because of the lack of a consistent definition of unlearning, a persistent problem remains. This study: (a) collected information about successful unlearning, and (b) demonstrated unlearning requirements for knowledge change occurrences in the hearing healthcare field. Study results: Survey of fifty hearing-aid professionals assessed their successful unlearning during instrumentation advances. Practioners’ responses during instrument updating demonstrated three perceptions of successful unlearning- requiring previous knowledge base, awareness about the need for change, and possessing positive viewpoints about unlearning

Challenges of change: Technology ease or technology upset?

New knowledge learning that involves errorless task performance has become a key objective for healthcare organizations [Rushmer & Davies, 2004]. As knowledge changes to incorporate the use of computer systems, service delivery using the Electronic Health Record (EHR) has created unforeseen challenges for service providers and the organizations they serve. This challenge appears mainly to involve a change in actions, behaviors and mental models by providers using the EHR [Senge, 2006]. This is necessary for healthcare organizations if they want to remain competitive, improve the quality of care, and reduce costs. The challenge is to develop and implement this new knowledge from individual current competencies [Becker, 2004]. One group that is critical in meeting these challenges is the physicians. Work practice documentation has changed to include a technological focus. As physicians interact with EHR technology, it is important they have the ability to unlearn needed knowledge while maintaining intellectual capital for organizations [McDonald, 1997]

Does Unlearning Impact Interaction of EHR End-Users?

Organizations need to remain competitive in today’s marketplace. Technology change impacts knowledge competencies that require alteration quickly, to reduce operating costs, and eliminate human errors. Updating computer system documentation procedures require unlearning to maintain competency. Physician end-users possess specialized competencies, or knowledge base in documentation of patient data to the degree that these operations have become automatic. To change the knowledge base of practitioners, end-users must use intellectual capital to unlearn patient care EHR documentation. This study focused on competency change, with the perceptions and influencers of unlearning of old competencies during EHR updates

Introduction to the Minitrack on Reports from the Field: Knowledge and Learning Applications in Practice

Welcome to this, the 53rd Hawaii International Conference on System Sciences (HICSS) conference. This Reports from the Field Minitrack, under the Knowledge Innovation and Entrepreneurial Systems Track, proudly brings you the latest research focused on the application of innovation of knowledge management issues as reported by both researchers and practitioners alike. With the focus on application, this minitrack helps practioners and theorists alike. It is here we examine how theory informs and impacts practice as well as how practice can influence theory from the practioner perspective

Challenges of Change:Technological Ease or Technological Upset?

The Electronic Health Record (EHR) has created new challenges for service providers and healthcare organizations. They need to remain competitive, improve the quality of care, and reduce costs while providing quality patient care. The development and implementation of new knowledge from individual current competencies will be an ongoing focus for healthcare organizations and healthcare providers who use the EHR technology. Twenty-eight physicians were interviewed for this report in order to understand their perceptions EHR technology in knowledge change or technology inspired unlearning, during service delivery. A model is proposed to better understand the changes needed in patient care delivery systems as specific actions, behaviors, and mental models require continual updating. Through this analysis, we developed the model, Service Delivery Unlearning Paradigm, to suggest how change influences collaboration, technological ease, and technological upset. Recommendations for future research and actions for practitioners are suggested

Unlearning before Creating new Knowledge: A Cognitive Process.

Recent research expresses serious doubts on the \ concept of unlearning. It is argued that knowledge \ cannot be discarded or eliminated in order to make \ space for the creation of new knowledge. Taking into \ account the recent scepticism, we focus on the \ cognitive dimension of unlearning and propose an \ alternative conceptualization. Considering how far \ unlearning can go from a psychological/cognitive \ scientific perspective, we propose that unlearning is \ about reducing the influence of old knowledge on our \ cognitive capacity. This study: (a) investigates the \ unlearning process within the cognitive domain and \ on an individual level and (b) proposes unlearning \ process triggers that detract or facilitate the \ knowledge change process, which could subsequently \ contribute to unlearning on an organizational level