In-App Reflection Guidance: Lessons Learned Across Four Field Trials at the Workplace

Fessl, Angela; Wesiak, Gudrun; Rivera-Pelayo, Verónica; Feyertag, Sandra; Pammer, Viktoria

doi:10.1109/tlt.2017.2708097

Cited by 18 publications

(15 citation statements)

References 32 publications

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“…One avenue for supporting this data-collection could be the design of reflection prompts [14], attached to the elements of the representation as a qualitative support to increase the decision basis for the DDBM design team. Asking questions on business model design was researched as an evaluation approach for business models [17].…”

Section: Discussion and Outlookmentioning

confidence: 99%

A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

Fruhwirth

Pammer-Schindler²,

Thalmann

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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Data-driven technologies enable organizations to innovate new services and business models and thus hold the potential for new sources of revenue and business growth. However, such new data-driven business models impose new ways for unwanted knowledge spillovers. Current research on datadriven business models and knowledge risks provides little help to identify and discuss such novel risks within the innovation process. We have developed a network-based representation of data-driven business models within one case organization, where it helped to identify knowledge risks in the design process of data-driven business models. In this paper, we further evaluated the artifact through 17 interviews with experts from the domain of business models, data analytics and knowledge management. We found that the network-based representation is suitable to visualize, discuss and create awareness for knowledge risks and see types of data-related value objects and quantification of risks as two recommendations for further research.

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Section: Discussion and Outlookmentioning

confidence: 99%

A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

Fruhwirth

Pammer-Schindler²,

Thalmann

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…This could be explained by the following two facts. First, it is easier to describe (low-level reflection) or interpret an experience (medium level reflection) than to derive insights from reflection and put them in writing (high level reflection) [9]. Second, the experimental study (about 2 hours) may have been too far outside participant's real search practice for them to be able to derive deeper insights search behaviour.…”

Section: Discussionmentioning

confidence: 99%

“…Pammer et al [17] have shown that reflection on time log data incited users to generate insights about time management, and experiment with different time management strategies. Prior research has also shown that automatic reflection prompts can support reflective learning based on data: Fessl et al [9] implemented and evaluated reflection prompts that were embedded both directly within action, and with a larger temporal separation from action in informal and workplace learning contexts. The authors' reflection prompts reminded users to reflect, and pointed out salient data to users.…”

Section: Related Workmentioning

confidence: 99%

“Mirror, mirror on my search...”: Data-Driven Reflection and Experimentation with Search Behaviour

Fessl

Apaolaza

Gledson

et al. 2019

Lecture Notes in Computer Science

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Searching on the web is a key activity for working and learning purposes. In this work, we aimed to motivate users to reflect on their search behaviour, and to experiment with different search functionalities. We implemented a widget that logs user interactions within a search platform, mirrors back search behaviours to users, and prompts users to reflect about it. We carried out two studies to evaluate the impact of such widget on search behaviour: in Study 1 (N=76), participants received screenshots of the widget including reflection prompts while in Study 2 (N=15), a maximum of 10 search tasks were conducted by participants over a period of two weeks on a search platform that contained the widget. Study 1 shows that reflection prompts induce meaningful insights about search behaviour. Study 2 suggests that, when using a novel search platform for the first time, those participants who had the widget prioritised search behaviours over time. The incorporation of the widget into the search platform after users had become familiar with it, however, was not observed to impact search behaviour. While the potential to support un-learning of routines could not be shown, the two studies suggest the widget's usability, perceived usefulness, potential to induce reflection and potential to impact search behaviour.

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“…In cognitive psychology, data from large scale evaluation can now be used to validate models derived from the cognitive psychology that are commonly only studied in the laboratory, such as how concepts are formed in self-directed learning (Seitlinger et al, 2020). For intelligent systems, some general implications have been derived in terms of what models are involved (e.g., knowledge base, learner model, adaptation model), how they can be formalized and applied, e.g., by providing adaptive prompts for reflection (Fessl et al, 2017).…”

Section: Interdisciplinaritymentioning

confidence: 99%

Interdisciplinary Doctoral Training in Technology-Enhanced Learning in Europe

et al. 2020

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Technology enhanced learning (TEL) research connects Learning Sciences, Educational Psychology, and Computer Science, in order to investigate interventions based on digital technologies in education and training settings. In this paper, we argue that doctoral training activity for TEL needs to be situated at the intersection of disciplines in order to facilitate innovation. For this, we first review the state of disciplinarity in TEL, reviewing existing meta-studies of the field. Then, we survey 35 doctoral education programs in Europe in which doctoral students working on TEL topics are enrolled. Findings indicate that most doctoral schools are associated with a single discipline and offer methodological rather than content-specific modules. TEL-specific content is provided only in exceptional cases, creating a potentially isolating gap between master-level education and scientific conferences. On this background, we argue that cross-institutional doctoral training is important to progress TEL as a field. In this article, we study and share the approach of an international doctoral summer school organized by the European society EA-TEL over the past 15 years. The summer school provides foundational methodological knowledge from multiple disciplines, contentspecific topical knowledge in TEL, access to cutting edge scientific discourse, and discussion of horizontal issues to doctoral students. We further provide an analysis of shifting program topics over time. Our analysis of both, institutional as well as crossinstitutional doctoral training in TEL, constitutes this paper's core contribution in that it highlights that further integration of perspectives and knowledge is to be done in TEL; together with codification and explication of knowledge in the intersection of disciplines.

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In-App Reflection Guidance: Lessons Learned Across Four Field Trials at the Workplace

Cited by 18 publications

References 32 publications

A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

A Network-based Tool for Identifying Knowledge Risks in Data-Driven Business Models

“Mirror, mirror on my search...”: Data-Driven Reflection and Experimentation with Search Behaviour

Interdisciplinary Doctoral Training in Technology-Enhanced Learning in Europe

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