A Tutorial Markov Analysis of Effective Human Tutorial Sessions
This paper investigates what differentiates effective tutorial sessions from less effective sessions. Towards this end, we characterize and explore human tutors{'} actions in tutorial dialogue sessions by mapping the tutor-tutee interactions, which are streams of dialogue utterances, into streams of actions, based on the language-as-action theory. Next, we use human expert judgment measures, evidence of learning (EL) and evidence of soundness (ES), to identify effective and ineffective sessions. We perform sub-sequence pattern mining to identify sub-sequences of dialogue modes that discriminate good sessions from bad sessions. We finally use the results of sub-sequence analysis method to generate a tutorial Markov process for effective tutorial sessions.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Demo2Tutorial: From Human Experience to Multimodal Software Tutorials
Human experience in digital environments offers a vast, underexplored resource of authentic, untrimmed interactions that contain rich procedural knowledge. We introduce Demo2Tutorial, a framework that transforms this exp…
"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans
To support human decision making with machine learning models, we often need to elucidate patterns embedded in the models that are unsalient, unknown, or counterintuitive to humans. While existing approaches focus on exp…
Decision MakingLevel Up Your Tutorials: VLMs for Game Tutorials Quality Assessment
Designing effective game tutorials is crucial for a smooth learning curve for new players, especially in games with many rules and complex core mechanics. Evaluating the effectiveness of these tutorials usually requires …
A Tutorial on the Spectral Theory of Markov Chains
Markov chains are a class of probabilistic models that have achieved widespread application in the quantitative sciences. This is in part due to their versatility, but is compounded by the ease with which they can be pro…
Hidden Markov Model: Tutorial
This is a tutorial paper for Hidden Markov Model (HMM). First, we briefly review the background on Expectation Maximization (EM), Lagrange multiplier, factor graph, the sum-product algorithm, the max-product algorithm, a…
Action RecognitionBayesian InferenceBayesian Optimisationmodel+5