Scientific Reasoning Task
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A Scientific Reasoning Task is a empirical reasoning task that requires empirically validatable knowledge.
- AKA: Scientific Discovery, Scientific Learning.
- Context:
- output: an Abstract Model (based on empirically validatable knowledge).
- It can range from being a Empirical Research/Applied Research/Applied Science to being a Theoretical Research/Basic Research/Theoretical Science.
- It can be performed by a Scientific Reasoning System (such as a scientific researcher who follows scientific reasoning algorithm).
- It can be instantiated in a Scientific Research Act.
- It can be studied Science Discipline.
- It can be reported in an Academic Forum (such as an academic conference or academic journal).
- Example(s):
- … to understand living system heredity.
- a Predictive Modeling Task.
- …
- Counter-Example(s):
- an Engineering Task.
- a Manufacturing Task.
- a Design Task.
- See: Knowledge, Social Sciences Research, Humanities Research, Scientific Data Mining Task.
References
2009
- (WordNet, 2009) ⇒ http://wordnetweb.princeton.edu/perl/webwn?s=scientific%20research
- S: (n) scientific research, research project (research into questions posed by scientific theories and hypotheses)
- http://en.wiktionary.org/wiki/scientific_research
- 1. Research performed using the scientific method.
1998
- (Jong et al., 1998) ⇒ Ton de Jong, and Wouter R. Van Joolingen. (1998). “Scientific Discovery Learning with Computer Simulations of Conceptual Domains." Review of educational research, 68(2).
- ABSTRACT: Scientific discovery learning is a highly self-directed and constructivistic form of learning. A computer simulation is a type of computer-based environment that is well suited for discovery learning, the main task of the learner being to infer, through experimentation, characteristics of the model underlying the simulation. In this article we give a review of the observed effectiveness and efficiency of discovery learning in simulation environments together with problems that learners may encounter in discovery learning, and we discuss how simulations may be combined with instructional support in order to overcome these problems.
1989
- (Howson & Urbach, 1989) ⇒ Colin Howson, and Peter Urbach. (1989). “Scientific Reasoning: The Bayesian Approach." Open Court Publishing,
1987
- (Chandrasekhar, 1987) ⇒ Subrahmanyan Chandrasekhar. (1987). “Truth and Beauty: Aesthetics and Motivations in Science." University of Chicago Press Chicago.