MACHADO, Marcelo de Oliveira Costa; ASSIS, Elias Cyrino; SOUZA, Jairo Francisco; SIQUEIRA, Sean Wolfgand Matsui. A framework to support experimentation in the context of Cognitive Biases in Search as a Learning process. In: XX Brazilian Symposium on Information Systems (SBSI), 20. , 2024, Juiz de Fora/MG. Proceedings […]. New York: Association for Computing Machinery, 2024 . Article No. 39, p. 1-9. DOI: https://doi.org/10.1145/3658271.3658310.
A framework to support experimentation in the context of Cognitive Biases in Search as a Learning process
Authors
Marcelo de Oliveira Costa Machado (UNIRIO)
Elias Cyrino Assis (UFJF)
Jairo Francisco Souza (UFJF)
Sean Wolfgand Matsui Siqueira (UNIRIO)
Abstract
Context: Information seeking plays a key role in the learning process, enabling individuals to acquire knowledge and make well-informed decisions. However, this process is not exempt from cognitive biases that can distort the way we interpret and use available information. Ongoing research seeks to comprehend and mitigate these biases to enhance search efficacy and promote effective learning.
Problem: Despite these efforts, existing empirical experimentation remain confined to isolated platforms, hindering reproducibility and collaborative progress within the field. This limitation underscores a critical need for a more unified approach to experimentation.
Solution: In response, we propose a comprehensive framework designed to support and standardize experimentation.
IS theory: Our approach aligns with Design Theory, establishing a connection between cognitive biases and the technical dimensions of the information system.
Method: To define the requirements of the proposed framework, a thorough literature review on cognitive biases in search was conducted. The framework’s efficacy is demonstrated through a proof of concept.
Summary of Results: We showcase the framework applicability by instantiating it with a study on confirmation bias within a health-related search task. This implementation is particularly relevant as it integrates crucial components and requirements identified in previous research.
Contributions and Impact in IS area: Our proposed framework bridges a significant gap in the field by presenting a standardized approach to conducting experiments on information seeking and cognitive biases. This not only fortifies the reliability of individual studies but also fosters collaborative efforts, enabling a more profound understanding of information-seeking behaviors across diverse domains within the Information Systems community.
Keywords:
Confirmation Bias, Heuristics, Interactive Information Retrieval, Search as Learning.
