In this paper we try to organize machine teaching as a coherent set of ideas. Each idea is
presented as varying along a dimension. The collection of dimensions then form the …

Temporal point processes (TPP) are probabilistic generative models for continuous-time
event sequences. Neural TPPs combine the fundamental ideas from point process literature …

The objective of personalized learning is to design an effective knowledge acquisition track
that matches the learner's strengths and bypasses his/her weaknesses to ultimately meet …

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 …

Spaced repetition is among the most studied learning strategies in the cognitive science
literature. It consists in temporally distributing exposure to an information so as to improve …

In a wide variety of applications, humans interact with a complex environment by means of
asynchronous stochastic discrete events in continuous time. Can we design online …

Ongoing digital transformations facilitate the conduct of online courses and distance
learning. In this study, it was aimed to investigate the role of learners' personalities and …

Since the 1960s, researchers have been trying to optimize the sequencing of instructional
activities using the tools of reinforcement learning (RL) and sequential decision making …

OBJECTIVE To describe the modified operational plan we implemented for residents and
faculty in our orthopedic surgery department to allow continuation of resident education and …

Microlearning is all the rage, but what is it exactly? What does a successful microlearning
object look like? And, how sound are the pedagogical practices surrounding microlearning …