Contradiction and Abduction
The increasing use of data in educational research, framed within fields like Eduinformatics, necessitates effective strategies for hypothesis generation within the cyclical data-driven and hypothesis-driven approach. However, the crucial step of forming novel hypotheses often relies on Abduction, a form of inference known to be challenging. This paper addresses the difficulty of abductive hypothesis formation by exploring potential aids. Through conceptual analysis grounded in Eduinformatics and IR Philosophy, we investigate the role of contradiction in facilitating this process. We argue that constructively engaging with contradictions—whether they arise from data conflicting with existing theories or from differing normative viewpoints—serves as a powerful catalyst for the "surprise" that triggers abduction. The development of the Significant Other Groups (SOGs) concept is presented as an illustrative case where analyzing contradiction led to new theoretical insight. This study concludes that reframing contradiction not as an obstacle but as a vital prompt for inquiry offers a valuable perspective for enhancing creativity and knowledge generation, thereby aiding abduction within the research cycle in Eduinformatics. This perspective helps reconstruct the cycle linking hypotheses and data by leveraging the generative power inherent in contradiction.
Authors
- Kenya Bannaka
- Sayaka Matsumoto (ORCID: https://orcid.org/0000-0002-4556-0744)
- Masato Omori
- Yasuo Nakata
- Kunihiko Takamatsu
- Yasuhiro Kozaki
- Masao Mori
- Katsuhiko Murakami (ORCID: https://orcid.org/0000-0002-1923-4259)
- Kenichiro Mitsunari
- Aoi Kishida (ORCID: https://orcid.org/0000-0002-8637-5684)
- Tsunenori Inakura (ORCID: https://orcid.org/0000-0003-4596-6178)
- Shotaro Imai
- Ikuhiro Noda
Institutions
- Osaka Kyoiku University (JP)
- Kobe Tokiwa University (JP)
- Shanghai Institute for Science of Science (CN)
- Kobe City Nishi-Kobe Medical Center (JP)
- Institute of Science Tokyo (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- IIAI Letters on Institutional Research
- Published
- 2025-01-01
- DOI
- https://doi.org/10.52731/lir.v005.471
- Primary Topic
- Statistics Education and Methodologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Japan Society for the Promotion of Science