An approach to model forgetting

This paper aims to investigate the possibility to include aspects of forgetting into business process modeling. To date, there is no possibility to model forgotten or to-be- forgotten elements beyond the mere deletion. On a first attempt, we focus on the individual level and model knowledge transformation within a single person. Using the Knowledge Model Description Language, we propose ways to include different forms of forgetting into the realm of modeling tools. Using data from an experimental setting within an assembly line production environment, the usability of those new modeling tools is tested. So far, the applicability of modeling features for forgetting on the individual level is mostly restricted to a research context. However, clear requirements to transfer the tools onto the team- and organizational level are set out.

Evaluation of Self-Reflection Training to Uncover Tacit Knowledge in a Learning Organization

By working in different projects and different teams over years, employees acquire tacit knowledge unconsciously. It is represented through experiences and is intangible. This knowledge is embodied in our routines. Therefore, it is difficult to verbalize tacit knowledge. This paper introduces a practical approach for companies to use their tacit knowledge in order to become a learning organization. The results of a semi-standardized face-to-face-interview survey with participants (n=10) show to what extent a self-reflection can contribute to uncover and share tacit knowledge in an IT-organization. The answers of the participants were recorded, utilized, coded and analyzed qualitatively. The results show that the intervention can encourage the process of uncovering tacit knowledge. It is possible for the employees to see the past project problems from different perspectives via self-reflection. Thereby they are able to uncover the tacit dimension of their experience and gain new insights.

Intentional Forgetting in Socio-Digital Work Systems

Future work environments offer numerous technical applications to manage increasing amounts of information for organizations, teams, and individuals. Psychological concepts of intentional forgetting (IF) can be applied to improve the performance of work systems or to extend cognitive capacities of humans in technical systems. Different IF mechanisms have been suggested for assisting technology-aided IF, such as: (1) filtering of irrelevant or distressful information (e.g., by suppressing, deleting, or selecting), (2) delegating tasks from human to digital agents, changing roles, and reorganizing socio-digital work systems, or (3) systematic (re-)placement of retrieval cues or triggers to generate or suppress behavior. Due to these different underlying IF mechanisms, the implementation of IF at individual, team, and organizational level will differ substantially between work areas or systems. In order to gain a better understanding of how socio-digital applications of IF impact human behavior and reactions, it is necessary to (a) differentiate between relevant characteristics of socio-digital IF systems and (b) gain an understanding of how these characteristics impact users’ attitudes and performance. Thus, the present paper aims to classify and compare these characteristics of different applications of IF and introduces variables and methods to study psychological effects on users’ behavior, experience, and affective reactions.

Advanced Memory Buoyancy for Forgetful Information Systems

Knowledge workers face an ever increasing flood of informa- tion in their daily lives. To counter this and provide better support for information management and knowledge work in general, we have been investigating solutions inspired by human forgetting since 2013. These solutions are based on Semantic Desktop (SD) and Managed Forgetting(MF) technology. A key concept of the latter is the so-called Memory Buoyancy (MB), which is intended to represent an information item’s current value for the user and allows to employ forgetting mechanisms. The SD thus continuously performs information value assessment up- dating MB and triggering respective MF measures. We extended an SD- based organizational memory system, which we have been using in daily work for over seven years now, with MF mechanisms directly embedding them in daily activities, too, and enabling us to test and optimize them in real-world scenarios. In this paper, we first present our initial version of MB and discuss success and failure stories we have been experiencing with it during three years of practical usage. We learned from cognitive psychology that our previous research on context can be beneficial for MF. Thus, we created an advanced MB version especially taking user context, and in particular context switches, into account. These enhancements as well as a first prototypical implementation are presented, too.

A Web-Based Information System to Evaluate Different Versions of IT Artefacts in Online Experiments

Design science research is a common research method in the field of information systems (IS), as it bridges the gap between IS research and practice. The outcome of design science research are artifacts, which – besides others –can be prototypical applications, so-called IT artifacts. When such IT artifacts are evaluated as part of a design science research cycle, questionnaires and inter- views are a commonly used method. We have integrated the demonstration and evaluation phase of a web-based IT artifact, by developing a web-based infor- mation system which integrates both a web-based prototype with a questionnaire system. Our information system supports multiple studies, different versions of the IT artifact and several question-specific and participant-specific configura- tion options.

Hiding to hedge against information overload

Many workspaces nowadays overload people with information – often with information that is irrelevant to the task at hand. Such information cannot only be distracting but additionally misleading, and can potentially impair the performance in relevant tasks. Here we set out to investigate how higher order cognition is influenced by such irrelevant or misleading information. Specifically we were interested in disentangling distraction effects due to task-irrelevant information from distraction effects due to misleading associations. To this end, we examined the solution rates for Remote Associates Test (RAT) items as a function of the presence of additional irrelevant or misleading word material, presented alongside the RAT items. Solving these kinds of word riddles is considered higher cognition as it is closely related to problem solving in real world scenarios. Additionally we manipulated the expectation of participants towards the nature of additional information across two experiments. In Experiment 1 participants believed that all additional words were irrelevant. In Experiment 2 they thought some of the information might be useful for their task. Alongside other manipulations we hereby ensured an attentional focus on the additional information in Experiment 2. Results showed, participants performed poorer in solving RAT items when irrelevant or misleading words were presented along with the RAT items compared to no additional presentation. Moreover misleading information was additionally interfering, but only if attentively processed. To avoid such distraction and misdirection, future personal information systems like the Semantic Desktop [1-2] can help by detecting and hiding temporarily irrelevant or misleading information.