(A message to my students, sharing publicly because it can help others understand what commenting actually is about …. it’s often done wrong.) I realized I didn’t instruct you properly on how to “edit and comment” papers. I want to fix my mistake. When we talk about “edit and comment”, we don’t mean proof-reading. Proof-reading is the least important part.…
Let’s start from evaluation. When have a computer that does something, we want to see if it does it well. So, this (“seeing if it does well”) is called evaluation. Evaluation is at the core of pretty much every computational technique, such as algorithm, model, system, device, etc. We want these things to work and improve people’s lives. And that…
A major problem in user studies are high SDs (=standard deviation). People generally experience and perceive things differently. This imposes problems for statistical analysis of user study data, because methods are often based on means, e.g., means comparison (t-test, ANOVA). Consider two cases: participant A gives on a five-point likert scale the rating 5 to a system (maximum), participant B…
Been playing chess recently. Chess is oddly similar to research. Thinking and writing require steps similar to moving pieces on board, with eventually the paper you’re writing being the board. Concepts and sentences are the pieces. You need to move them into the correct order (position) on the board. And there is a similar goal of making the opponent (reviewer)…
In addition to generating it (!), AI can be used for *detecting* empty rhetoric. Is the sentence below empty rhetoric? “By addressing both intrinsic and extrinsic motivational factors, AI-based chatbots can play a key role in creating effective learning environments.” >> Yes, it’s empty rhetoric – the sentence sounds academic but conveys no real substance: >> It makes a sweeping…
evaluation complexity increases when: *task is more subjective*you have more coders*you have more categories*you have more data to code chance-adjusted agreement (as opposed to percentage agreement) metrics typically aim to consider these factors in their calculation (though there’s no easy way to quantify “subjectivity” except after the calculation; a low score can be of indicative of the subjective nature of…
CHI research has become more complex (but not more insightful). The reason? Complexity is a competitive factor: it helps separate your paper from others. Lengthy papers with more substudies and details are more likely to do better than short but insightful work that might have more relevance for HCI theory and/or practice. Reviewers are instructed to pay attention to HCI…
The illusion of similarity: two papers (A and B) look the same.They have the same structure.They have the same number of words.Both use fluent, nearly flawless English.Both reference the same number of papers.They have the same number of tables and figures. For a layperson, both these papers look the same. Yet, one of them is the worst horsesh*t you’ve ever…
Observed myself citing various “superpowers” to my PhD students in occasional emails. So, thought of writing these down (the list might get updated). Currently, I can think of eleven research superpowers [updated: November 11, 2024]. Here they are, in no particular order. 1. SPECIFICITY Be specific. Applies pretty much to any form of communication: Being specific is one #researchsuperpower (but…
Three ways of justifying/arguing for research choices (e.g., hyperparameter values, thresholds, sample sizes):