Cross-Validation, Overfitting, and Validity

When building statistical models in educational research or predictive analytics, one of the most important considerations is ensuring the model generalizes well to new data. This blog will focus on two fundamental concepts: cross-validation and overfitting, and how they relate to ensuring model robustness. What is Overfitting? Overfitting occurs when your model fits not just […]

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Understanding Diagnostic Metrics for Regressors

In this blog post, we’ll explore some key metrics for evaluating regressors, including linear correlation, Spearman’s rho, mean absolute error (MAE), root mean squared error (RMSE), and information criteria like BIC and AIC. These metrics are vital in understanding the performance of regression models, especially in education and other data-driven fields. Linear Correlation: How Do […]

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Understanding Diagnostic Metrics for Classifiers: Accuracy vs Cohen’s Kappa vs ROC vs Precision and Recall vs F1

In machine learning and educational research, choosing the right metric to evaluate a classifier’s performance is critical. While many people are familiar with accuracy, there are other diagnostic metrics that provide deeper insights into how well a model is performing. In this blog, we’ll dive into two metrics: Accuracy and Cohen’s Kappa, explaining why accuracy […]

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How I Would Learn Digital Marketing

If you’re someone just starting out or considering a career in digital marketing, you’ll find countless resources. You could turn to platforms like YouTube, Udemy, or any other e-learning site and search for courses on Google Ads, SEO, Facebook Ads, Programmatic Advertising, Growth Marketing, and so on. You’ll likely be overwhelmed. So, let me walk […]

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Explainable AI (xAI) and Interpretable AI in Education

Artificial Intelligence (AI) is reshaping various fields, including education, but its complexity often leads to questions about trust, fairness, and transparency. In response, two crucial concepts have emerged: Explainable AI (xAI) and Interpretable AI. These terms may sound similar, but they offer distinct affordances and are critical in educational contexts where understanding predictions can drive […]

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Classification Algorithms

In educational data mining, prediction models play a critical role in analyzing student data to infer specific outcomes, known as predicted variables, from a combination of other features, referred to as predictor variables. These models are applied in various contexts: sometimes to forecast future performance, and at other times to gain insights into current states […]

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