In quantitative research, justifying sample size is a fundamental requirement. Yet, one of the most misused tools in this process is G*Power — a free and powerful program that helps estimate sample sizes based on power analysis.While G*Power is valuable, it’s often misapplied or overly relied upon, leading to flawed research designs, underpowered studies, and … Read more
Despite the growing acceptance and institutionalization of qualitative research in academia, many studies still fall into a critical trap — they lack a solid theoretical foundation. While qualitative methods are celebrated for exploring complexity, meaning, and lived experience, they are increasingly being used in ways that are conceptually shallow, methodologically misaligned, and analytically weak. This … Read more
Regression analysis is one of the most widely used statistical tools in empirical research. Yet, beneath many published models lies a silent killer of validity: the misuse of control variables. Too often, researchers include controls reflexively — without a clear understanding of their role in causal inference or model integrity. This article dives into what … Read more
In an era of publish-or-perish, identifying a “research gap” has become a standard ritual in academic writing. Yet, most so-called gaps are superficial at best — and misleading at worst. A weak gap leads to weak contribution. And this is where most researchers, including many doctoral candidates and early-career academics, unknowingly undermine their own work. … Read more
𝗜𝗺𝗽𝗮𝗰𝘁 𝗙𝗮𝗰𝘁𝗼𝗿 𝗢𝗯𝘀𝗲𝘀𝘀𝗶𝗼𝗻: 𝗪𝗵𝘆 𝗝𝗼𝘂𝗿𝗻𝗮𝗹 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗶𝘀 𝗡𝗼𝘁 𝗝𝘂𝘀𝘁 𝗔𝗯𝗼𝘂𝘁 𝗡𝘂𝗺𝗯𝗲𝗿𝘀 Too many researchers chase Impact Factor (IF) like it’s the holy grail of academic publishing — but this obsession often leads to poor strategic decisions and missed opportunities. 𝗛𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗺𝗼𝘀𝘁 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵𝗲𝗿𝘀 𝗶𝗴𝗻𝗼𝗿𝗲: – Impact Factor ≠ Article Quality — a journal’s prestige doesn’t … Read more
