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Logical Reasoning Training

The DCIT analytical reasoning approach has many advantages over conventional argument construction and analyzing inference approaches. For example, please consider the following benefits:

1. Students only need to learn one simple universally generalizable argument structure rather than the numerous types of inference and argument structures. Thus, there is no compelling practical need to master conventional modes of inference (e.g., deductive, inductive, abductive, presumptive, defeasible, analogy, formal logic, informal logic, argument schemes, etc.).

2. The DCIT approach automatically ensures that the inferential lines of reasoning constructed are structural correct and logical (e.g., well-formed). Structurally correct does not necessarily equate specifically to deductive validity which often is an unreasonable standard for much of the real-world problems.

3. The DCIT new argument structure constraints ensure that there are no hidden or missing inferentially linked premises (i.e., enthymematic arguments) which can weaken the assessed strength of the argument and hide flaws in the reasoning.

4. The DCIT approach is robust and rigorous so it easily accommodates any complexity of argument regardless of the (1) length (i.e., inference-upon-inference), (2) depth (i.e., multiple layers of inferential premises linked through an inferential matrix of supporting assumptions (e.g., ancillary evidence) all supporting a single conclusion, or (3) number of converging lines of inference supporting a single conclusion.

5. Since the DCIT approach uses simple, but transformative, modifications to a mode of inference (i.e., class-inclusion transitivity) that is intuitive and develops in early childhood, the typical audience to the presented argument can easily follow and understand the lines of inference in the argument presented with no formal training or background in argumentation. The capacity of the logic of the reasoning to be self-evident to any audience is crucial.

6. Logical relevancy¹ for an individual premise (e.g., item of evidence) is made readily apparent through its clear placement in the regimented overall argument structure.

7. The typical student challenge of distinguishing between serial or convergent lines of reasoning in a single argument structure analysis is easily overcome with the use of DCIT structural constraints.

8. The DCIT approach easily resolves questions of structural validity or well-formedness (i.e., both deductive or non-monotonic/defeasible).

9. Determinations of probative weight or force reaching the final conclusion are more easily assessed.

10. The argument structure makes readily apparent the important necessary distinction between inferentially linked premises and supporting non-inferentially linked assumptions (i.e., necessary and ancillary). For example, the sufficient sensory and memory capacity of a witness testifying at trial are necessary assumptions to support the acceptability of their witness testimony but those facts are not inferentially linked to the line of reasoning. They must be proven by separate lines of reasoning that are appropriately connected.

11. The seven types of argument objections or attacks (i.e., defeater, diminisher, rebuttal, undercutting, undermining, refutation, and attack on an attack are easily accommodated and depicted within the argument structure.

12. DCIT’s use overcomes overreliance on deduction and induction which often provide a limited and often inadequate inference tool kit for handling many complex real-world inferential problems.²

13. Its simple user-friendly templates, guidelines, and supporting embodied cognition visual language make using the DCIT approach easier to learn for typical high school students (e.g., MBacc) to PhD graduates. (For individuals already deeply steeped in conventional argument methodology, it can require a willingness to set aside old habits during the learning and practice phase. This usually happens very quickly once they see demonstrated the power of the DCIT approach compared to their conventional argument methods.)

14. DCIT’s companion use of a new unique metaphoric cognitively embodied argument visual language, the Logic-Briddge, facilitates student comprehension of such concepts of probative weight and force, argument strength, inference steps, well-formedness, logical relevancy, degrees of certainty or acceptability, burden of proof, objections, permissible inferences, etc.. Professors George Lakoff and Mark Johnson (e.g., “Metaphors We Live By”) demonstrate how a cognitively embodied metaphor connected to our physical senses and experience makes our understanding and use of such concepts greatly enhanced. For example, the “Probative Weight” lecture video prepared for the Cardozo Law School “Fact Investigation” class (https://vimeo.com/user8380252) makes easily appaent the power of that embodied metaphor to increase student comprehension and mastery.(To be clear, however, this DCIT curriculum is not about teaching argument mapping.)

15. DCIT’s companion use of a new unique metaphoric cognitively embodied argument visual language for argument diagraming (i.e., mapping) also resolves the fundamental flaws in conventional argument mapping (hierarchical tree-like) that has been the standard design for 200 years and is taught in many universities. Those flaws often result in erroneous reasoning.

16. The robust curriculum addresses all relevant “constructing argument” and “analyzing inferences” concepts and practices.

1 Logical relevancy is the determination of whether a fact to be proved provides an increase of acceptability by the fact-finder to the truth of the final matter at issue. Such a determination is an excellent assessment measure of these sub-competencies in students since it requires that the student correctly and persuasively demonstrate that the fact (e.g., item of evidence) logically fits within the overall inferential network of premises supporting the final conclusion and that the inference analysis shows that it has sufficient probative weight to increase the probability or degree of “acceptability” that the final conclusion is true. Since the inferential network can consist of multiple linked premises (i.e., inference-upon-inference for a number of iterations) along with supporting assumptions which are also themselves supported by inferences, the resulting inferential matrix for even a normal factual situation can be complex. DCIT makes that logical relevancy determination much simpler and easier.

2The inadequacies of standard logics (e.g., deduction and induction) for much of practical real-world reasoning is not a controversial position among argumentation scholars. In fact, it was a motivating factor, in part, for the development of “informal logic” and its dissemination in college classes starting in earnest in the 1970’s. (Woods, J., Ohlbach, H.J., Gabbay, D.M., & Johnson, R.H. (2002). Handbook of the Logic of Argument and Inference: The Turn Towards the Practical.)

Logical Reasoning Consulting

Our consulting practice typically focuses on improving the logical reasoning that underlies a particular project. Our in-depth inferential analysis reveals the strengths and weakness of the arguments, provides solutions, and transforms the actual text narrative to make the arguments most compelling. The subject matter can be a corporate proposal or report, expert witness report, PhD dissertation, policymaking analysis, scientific report or analysis, legal factual argument such as demonstrating argument relevancy (no legal advise is provided), or any other project where clear logical real-world thinking is needed.

Logical Reasoning Coaching

One-on-one coaching provides the fastest path to mastery of logical reasoning. We can quickly spot obstacles in the student’s approach or understanding and provide easy solutions. Our coaching approach is positive, encouraging, kind, and joyful. We emphasize the student’s strengths and comfortably support their areas of needed growth. The coaching can be broad in scope or focused on a particular challenge such as passing the GRE Analytical Task section or other upcoming test. And the student can be in high school, undergraduate school, graduate school, or Post-Doc PhD programs.