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Abstrato

The Chakraborty-Galatro (CG) Equation: A Probabilistic Approach to Predict Doctoral Success Likelihood

Sourojeet Chakraborty*

Doctoral attrition (DA) is a phenomenon of graduate students choosing to discontinue graduate studies and is universally encountered across all academic disciplines. Key parameters that are typically perceived as valuable by Ph.D. students are identified from a systematic literature review; and the Chakraborty-Galatro probabilistic equation is formulated to predict the likelihood of a successful Ph.D. experience, called the Doctoral Success Likelihood (DSL), thus minimizing; possibly eliminating DA. Our model provides prospective/novice graduates with a novel framework to self-assess and predict the success likelihood of their Ph.D. journey. Such a framework enables the graduate student to judiciously self-assess and make a rationally informed decision about their career, rather than taking a blind leap of faith. Our equation also accommodates force majeure circumstances (such as a pandemic, the bereavement of a loved one, mental health issues, etc.), which may significantly impact the time taken to graduate (TTD); leading to a candidate choosing to drop out. Such circumstances typically derail/delay doctoral progress, and can push an initially feasible set of probabilities, into an undesired “infeasibility triangle”. Higher the net probability values obtained from our equation, stronger the likelihood of an enriching Ph.D. experience. When periodically tracked, our proposed equation can also help students identify and calibrate their own doctoral experience, while capturing tangible feedback and perspectives for both students, and supervisors. One of the authors presents his own doctoral journey, applying the CG equation to evaluate DSL values for his Ph.D., over a three year self-assessment period.