Comparison And Analysis Of Two Reasoning Theories In Psychology

Write two reactions to the two papers you reviewed, including the following sections:

Summary: Summarize the problem the paper is trying to address / what it’s trying to model, and how they modeled it

Reaction: What are your thoughts about the approach used? What are its limitations and strengths? What should they have done differently?

Future Work: What unanswered questions were left by the paper? What future projects should be done to follow up to this work? How would you tackle such projects? 

Summary of 'Against Logical Form'

Modeling cognition and human reasoning remains a contentious topic in the field of psychology with different proponents coming with their model or base of reasoning. While some argue based on the theoretical perception, others focus more on the evidential form which draws much reasoning. A comparison on the two article shall be done while trying to compare the several approach to reasoning and providing a reaction to each of the models provided. The two articles highlight reasoning theories based on the different disciplines stated. The paper focuses on two articles under the topic while examining their view on the same through an analysis on the concepts provided, offering a reaction and recommendation for future work.

The text is provided by Johnson-Laird in presenting an argument against the logical form of reasoning. In the text, he opens up with an introduction to the text where a justification is provided linking the purpose of the study and the need for his opposition. The article provides supported work in part by the National Science Foundation which sought to carry out a study on the probabilistic and deductive reasoning. The article bases its argument on the core reasoning of logic and support for the same through evidential reasoning which supports the logical form. Psychologists in support of the reasoning view human reasoning in first recovering the logical form in a concept then followed by the application of rules of inference to draw a relation between the logical reasoning and the former.

However, the article argues against the form of reasoning and instead selects a different path towards reasoning. The authors that the logical form of reasoning transcends the grammatical forms of a sentence which are responsible in expressing the same as the logical form of reasoning depends on the context in place. In its reasoning, the article seconds an alternative where reasoning depends on the mental models thus raising the need for recovery of the logical form of reasoning (Johnson 202). The first step of reasoning bases on the establishment of a logical form in reasoning of a premise followed by the matching to corresponding formal rules of inference. The two processes justify reasoning where the first is evidenced by the second one in the case thus making a reasoning logical.

 Further, the article uses the example of a bank receiving a subsidy from a government in explaining the concept of reasoning. The argument forwarded in the text states that the logical form and the rules of inference have no role in the mental process operating in the daily life reasoning. Instead, reasoning is viewed as a way of drawing conclusions from a given set of proposition expressed in a natural language. The article further provides another theory of mental models which comes with a different approach to reasoning. The theory assumes that reasoning does not depend on logical forms but rather depends on mental models.

In this respect, it assumes that individuals make meaning of all words not only relying on the logical forms but go further to the grammatical structures in a sentence and other forms of knowledge in order to make a construction of reasoning. The several assumptions and facts expressed are discussed therein with the author carefully listing the examples to assist in the understanding the concepts expressed. Therefore, a conclusion only becomes valid if it considers all the factors expressed in a sentence with all the components placed therein. The article concludes with a set of views on the truth in the theories expressed with a list of references for further study.    

Reaction to 'Against Logical Form'

Reasoning based on evidence, as explained in the text seems to carry more weight as opposed to other forms of reasoning such as the one on probability. People are more inclined to accept reasoning based on evidence compared to cases where individuals providing reason based on assumptions on life concepts. Every occurrence must be justified according to the events leading to one rather than using probability in deducing reason. The type of reasoning expressed in the paper largely remains authentic and applicable to the present life scenario. People ought to reason based on logic and the evidence provided therein to become justifiable. Reasoning based on assumption has over time raised issues as opposed to those made based on deductive reasoning. The paper is strategic in outlining the mistakes perceived in reasoning where individuals commit a mistake by importing logic directly by relating it into a psychological theory and using the same in the process of reasoning. Further, the argument supports itself through the use of evidence where reasoning has to be based instead of focusing on a theory that bears no evidence from the latter case (Johnson-Laird 4). Everything that is reasoned by humans must be based on evidence in order for one’s reasoning to be justified.  

The article is authentic in its reasoning based on the evidence and demonstration of reasoning concepts given in the book. The article seems true from the reasoning based on the theories presented. The theory assumes that reasoning does not depend on logical forms but rather depends on mental models (Szab107). Logic does not determine reasoning but rather is determined by the mental models involved in a matter. The case presented depends on the principle of truth which reduces stress on the working memory by focusing on the evidence pointing to a given case. The failure to represent evidence in reasoning directly, according to the article results in a fallacy for a given fact finding in reasoning.

The article is trustworthy based on the use of references in justifying some of its theories and aspects. The authors write concepts and use references from other scholarly individuals contributing to the field of psychology thus justifying the argument. The good number and careful use of references in the case present an authentic reasoning which makes the further reading on the case easy for learners who would like to present further research on the topic. An article becomes important if the sources used are justifiable and coming from peer reviewed sources. Thinking and reasoning has been widely referenced to the previous works of other authors where a relation can be drawn from the several cases in justifying the argument presented.

The article presents a formal way of justifying its reasoning based on the several examples it sets in its path to reasoning. The use of examples in reasoning resonates well with individuals in the field of study as they instill understanding of the several components under review. The sequence in which they appear expressing different elements enhances understanding and open mind on the concepts under discussion (Galbraith 22). At first, the article presents the example of a bank being bailed out by a government through a subsidy program which explains the logic in the given case. Besides, in justifying the reasoning of thought, the authors present cases such as the conditional reasoning where if there is a triangle then there is a circle (Johnson-Laird 202). The concept assists in disputing the logical form of reasoning and draws much evidence to the truth in reasoning where the conclusion deduces from the evidence presented in a given case.

Summary of Other Paper

In relation to the concept of the conditional reasoning, it becomes wrong to assume that since a triangle exists, a circle must be in place. In the case, there is no evidence pointing to the given case but rather exists an assumption of its existence based on a previous existence of a circle.

The type of reasoning used in the case is essential in arguing and the proposition of a theory based on evidence in reasoning. The example of the flute further justifies and authenticates the reasoning based on evidence. The example further joins the rest in trying to prove reasoning based on evidence rather than on assumption of logic in a given case. The assumption that if one plays a musical instrument then one does not play a flute is a fallacy as there lacks evidence pointing to the same. However, the thought of reasoning in the context should base on the pure evidence towards reasoning where it can be deduced that one plays a given instrument, and a possibility of one playing other musical instrument relying on the evidence presented. If one does not exhibit the skills of playing one instrument, no assumption should be used in reasoning on the possibility of a skill in the same respect.

Furthermore, the article draws authenticity in the example of ‘Steve is in front of John’ in explaining reasoning (Johnson-Laird 210). Steve being in front of John can be true from a speaker’s point of view but at the same time wrong if it lacks evidence. The view can be false if there is evidence that both of the people mentioned stand with their backs facing each other. The type of evidence used in justifying reasoning is solely based on the fact that there needs to be an evidence to inform reasoning.          

Despite the positive aspects raised in the case, there are certain issues that fail to draw reasoning in the path of logic. The reasoning based on evidence largely remains scanty in the daily life. People use probability in cases where reasoned evidence is absent. The research remains silent in the support of such cases thus leaving a gap in the step individuals should take in the case of lack of evidence. Lack of evidence should not lead to lack of reasoning as humans must reason even based on the probability of something happening. Relation and reasoning based on drawn conclusion must occur thus giving room for life to move on. For instance, a court of law uses evidence in reasoning and coming up with a judgment. However, in the lack of evidence but the presence of logical reasoning based on previous understanding of a case, a judge can decide on the way forward using the probability of some information being true. As a result, the research falls short of reasoning in the case where lack of evidence exists. Alternatively, there was a need to highlight the possibility but draw focus to the prime thought or theory upon which it based reasoning. In so doing, it would be developing a different thought process while at the same time recognizing the existence of the different model.

Reaction to Other Paper

The article was influential in the use of examples to drive meaning in the reasoned opinion presented in the case. The use of evidence in reasoning seems to appeal to most individuals and thus would experience a high uptake level. Reasoning based on facts that can be seen becomes easy and can be used to determine occurrences in different setups. However, the question of lack of evidence was left out which would contribute immensely to understanding their argument while recognizing the existence of a different case (Mueller 8). In as much as it is good to present one’s thought, it becomes largely contenting for one to discredit a given thought process in reasoning while not acknowledging that the process of reasoning can be done on a probability mood (Evans 18). As such, there is a need for future research and reporting by the authors to substantiate their thought or voice in the process of reasoning logically in the absence of evidence. The realty in daily life is that people can reason and make conclusions about several aspects of life without an existing evidence provided other suggestive options point towards the same. Future work should be in presenting and further supporting their idea while acknowledging the existence of other cases. In so doing, it should draw recognition while pointing to the accuracy of its reasoning without disregarding the former reasoning presented in the case.   

The article is a creation of Naveen Sundar, Govindarajulu and Selmer Bringsjord in 2017, contributing to the logical reasoning system. An introduction into the field of study and aspects discussed are highlighted in the case with an abstract touching on the reason for the article. The summary presents a different model or approach of handling given uncertainty in a first-order modal logic. The use of probabilistic approach has over time existed and used to justify operations where evidence cannot be seen easily unless some mathematical operations are conducted. Article presents its new logic in both diagrammatic and theoretical concept where the systems are based on both the probability theory as well as the proof theory. The theory presented cements the propositions brought forward by Chisholm basing on the primitive and undefined concept of reasoning in both the probability and proof theory.

Further, the article explains on the importance of its invention where its system can be used in cases where an interaction is needed by humans in providing a justification for uncertainties (Govindarajulu and Selmer 3). The case provides an example of the system in the provision of a solution to the paradox in a lottery. An explanation is offered therein in explaining the use of the concept in solution provision for values in counterfactual statements. Such statements are essential in offering explanations for occurrences where actions have to be explained to the users.

Further, the article takes the mathematical approach in drawing meaning where several sketches of algorithm are used in explaining reasoning demanding for the extension of first order resolution. Several calculus operations have been used to draw meaning to the case of reasoning that occurs for the probability and proof theory in reasoning. The article presents an explanation of the prior work where automated calculations are explained. Most of the aspects discussed relate to the automated errors in reasoning in machines and thus try to provide a solution or reasoning to the end users (Govindarajulu and Selmer 2). The uncertainty system is explained using the strength factors used to explain the probability theory of occurrences. The strength factors are divided into three concepts where there is the acceptable model, presumption, and beyond reasonable doubt model of occurrences. The article provides different clauses and their respective explanation and their applicability to the probability theory.

Future Work

 Further, it offers the usage of the system developed using its application in solving problems in the lottery paradox. The application is essential in explaining occurrences some of which are untrue but need explanation in a formal manner (Lisitsin, Alok and Campbell 750). The different strengths in beliefs are used to explain the paradox in the lottery paradox and present a solution to the same.

The application of the same in a murder solving is explained in the video game where different evidences are offered pointing to the same. The paper sums up with the conclusion and future study where it mentions the steps provided in explaining the proof and probability theories in solving foundational problems. Challenges experienced are outlined and recommendation given in improving and simplifying the same. Finally a reference to the material used in the context is offered which simplifies the understanding and provides a leeway to further dispensation of information.

Psychology uses several theories in explaining the reasoning aspect in humans. The article has provided a different approach in explaining the same using the computation model in finding reason for the probability and proof theory. The use of the proof theory has been well advanced in the article according to the original development of the theory. Proof theory does not rely much on the textual information but rather on the proof system justified by the use of mathematical objects. The article satisfies the requirements through its use of trees and calculus operations that are constructed in accordance to the rules of inference in the logical system of thought.

Moreover, the explanations offered follow the forms of representation such as the graphs and diagrams which support the sentential representation required in the proof theory. The article follows details needed in the proof theory and uses the best approach encompassing the Euler Diagrammatic System with all features remaining present. For instance, the article uses the inclusion and exclusion system where the relations have been displayed in the diagram between circles and points. At the same time, the inference rules are adhered to in the forms used in manipulating the diagrams. Thirdly, the formulas given justify the proof theory as it uses the application of developed theoretical techniques expressed in diagrammatical reasoning.   

The probability of winning in a lottery can be explained using the model while the proof for the same offered using the latter theory. The explanations offered in the case point to the applicability of the theory though to less wide extents. The resolution-based first order reasoning used in the system is strategic enough in making progress to the explanations used in mathematical operations (Bozzelli 310). The mathematical approach in explaining reasoning is essential in the cases where data is insufficient in driving truths in given situations. The article is well crafted and data presented in a logical manner that can be understood. The use of figures for the operations assists in fostering understanding in the case.

  At the same time, theoretical explanations have been offered to support the content illustrated in the figures. Observation on the type of work indicates professionalism which drives the authenticity in the case. The use of references in the case is justified as the sources relate to peer reviewed work which draws substance to the field of psychology in reasoning. Use of references assists in further reading and driving the need for research for contribution in further reasoning theories (Thom 13). Further, the authors openly identify difficulty in their research and point out the same.

Conclusion

The concept of mathematical approach is essential in finding meaning in reason. Provision of reason as exampled in the case of a lottery is purely based on calculations upon which profits occur for the players as well as that of the owners. Every time one fails a game, reason can be given by performing the mathematical calculations to direct reasoning that satisfies the concerned parties. According to the cognitive models, a person cannot purport to assign propositions to a given operation where the likelihood of the same happening violates the theory of probability.

 In this case, probability in reasoning must be based on the use of evidence in justifying various occurrences. In such as case, it would become easy to term one’s reasoning as false if the reasons given base on probability without a mathematical operation. Besides, giving mathematical reasoning would not resonate well with many individuals thus raising doubts and cases of distrust (Pearl 22).  The approach used by the writer remains practical and evidence provided through the steps used to arrive at the best result. The article serves the purpose of players in the betting industry and those in need of reasoned thoughts in cases where one understands that the reasons given are purely non-authentic. The probabilistic approach assists in handling the various cases occurring in the article thus draw much relevancy to the case. Therefore, the article remains relevant in the field of reasoning as it gives evidence to the probability that occur in given circumstances.

In this case, it assists learners and researchers in trying to find solutions to the stated issues thus contributing immensely to the works. The explanations are clear and each step in the calculus operation displayed appropriately. The operations serve well in the estimation of degrees of probability and providing actual figures for certainty (Govindarajulu and Selmer 2). For instance, it strategically explains the lottery problems to users who can then deduce the likelihood of their win or lose in a given session. The counterfactual statements can be further understood in the presentation despite denying the locals who fail to find meaning in the same.

Despite the positive elements in driving meaning in different cases, the application remains limited in use in the field of psychology. The article in itself finds difficulty in the first order logic and thus recommends for the resolution based first order in understanding the operations in solving non-trivial tasks (Govindarajulu and Selmer 2). Reasoning as a subject in psychology ought to be understood and explained in plain form to find meaning. However, the same is limited based on the approach used which focuses on mathematical operations. The use of mathematical approach in the case in explaining the reasoning limits individuals in the field of psychology where a good number of them do not have a proper mathematical grasp or knowledge.

As such, it becomes difficult to have the concepts explained and understood plainly by individuals. Proof to the difficulty can be explained by observing the probability and proof theories explained by other authors in the theoretical manner using text and examples in text form as opposed to the mathematical operations. The limitation reduces the number of persons interested in finding meaning unless if one falls within the professional field conversant with mathematical operations. Despite its in-depth approach to explanation, it fails to satisfy most of readers thus creating a disinterest among learners.      

References

The probability and the proof theory have been well-illustrated in the context. The expression on the text is alright and well covered according to the guideline and mathematical approaches used in the probability and proof theories of reasoning. There is a need for future work to incorporate other models and areas of the economy where the formula and approaches can be used to enhance use of the theory. Besides, much focus needs to be channeled in explaining the ways in which the probabilistic model can be used and its advantages rather than outlining its operation alone. As a matter of fact, non-probabilistic models appear to be much effective and simpler modes of application.

In this respect, simplification and overly explanation would assist in making the approach easy to use for individuals to reap the benefits of the theory. The article touches on most components needed for the operation. However, future work has to be done in providing more examples to drive meaning to the theories mentioned therein. The fact that the authors have identified challenges and mentioned in the further reading area suggests a lot for improvement. There is limited information on the topic that seems wide enough and difficult to interpret to a section of users accessing the content.

Much of theoretical and textual explanation has to be offered to benefit both learners with knowledge in calculus operations and those deprived of the same. The authors need to improve on the delivery means to provide ease in understanding through further examples where the probability theory can be applied (Granhag and Hartwig 233). Proof theory seems to have wide information but need further explanation to make it applicable using the system developed. The system touches on the counterfactuals and thus cannot be trusted to provide real data as in other cases where proof theory is used with supporting evidence. There is a need to make the theory more authentic in the case. The present work is awesome but can be further boosted to drive meaning and applicability with much more understanding of the content. More research has to be done and a possible inclusion of researchers in the similar field enjoined to product a much more substantial work in the future.       

Conclusion:

The two articles are strategic to the field of psychology and much more in theories of reasoning. The information offered in both cases have some academic benefits to the learners due to their authentic and operational approaches where various fields of applicability are explained. The two articles are instrumental in explaining the process of reasoning and drawing meaning to different approaches of reasoning.

However, the first approach seems much easier based on evidence compared to the probability theory which involves several calculations which may be difficult for individuals to use. As a matter of fact, individuals would rather prefer to use the first approach in deriving meaning rather than the second which needs skills in mathematical operations. Due to this, much improvement and learning has to occur to increase the usage of the mathematical approach which lots of individuals tend to neglect (Jarry 23). Despite their variances and limitations, both contribute immensely to the field and assist in understanding the reasons behind human.

Reference:

Pearl, Judea. Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, 2014.

Granhag, P. A., and M. Hartwig. "The strategic use of evidence technique: A conceptual overview." Detecting deception: Current challenges and cognitive approaches(2015): 231-251.

Bozzelli, Laura, et al. "Refinement modal logic." Information and Computation 239 (2014): 303-339.

Evans, Jonathan St BT. The Psychology of Deductive Reasoning (Psychology Revivals). Psychology Press, 2013.

Galbraith, Niall, ed. Aberrant Beliefs and Reasoning. Psychology Press, 2014.

Govindarajulu, Naveen Sundar, and Selmer Bringsjord. "Strength Factors: An Uncertainty System for a Quantified Modal Logic." arXiv preprint arXiv:1705.10726 (2017).

Johnson-Laird, P. "Against logical form." Psychologica Belgica50.3-4 (2010).

Johnson-Laird, P. N., Sangeet S. Khemlani, and Geoffrey P. Goodwin. "Logic, probability, and human reasoning." Trends in cognitive sciences 19.4 (2015): 201-214.

Kolodner, Janet. Case-based reasoning. Morgan Kaufmann, 2014.

Lisitsin, Vladimir A., Alok Porwal, and T. Campbell McCuaig. "Probabilistic fuzzy logic modeling: quantifying uncertainty of mineral prospectivity models using Monte Carlo simulations." Mathematical Geosciences 46.6 (2014): 747-769.

Mueller, Erik T. Commonsense reasoning: an event calculus based approach. Morgan Kaufmann, 2014.

Szabó, Z. "Against logical form." Donald Davidson on truth meaning, and the mental (2012): 105-126.

Thom, Paul. Medieval Modal Systems: problems and concepts. Routledge, 2017.

Jarry, Christophe, et al. "Apraxia of tool use: more evidence for the technical reasoning hypothesis." Cortex 49.9 (2013): 2322-2333.